A McKinsey report suggests that 78% of customers are more likely to return to a brand that offers a personalized experience.

While the right product recommendation can improve sales, building customer relationships is far more important for brands who want to make their business sustainable.

This is why the focus should be shifted to building the synergy between online and offline user experience. And that’s where product recommendations based on past purchases come into play.

What is omnichannel engagement?

Say you have purchased a dress from a physical store and later bought an accessory from the online app of the same store. The recommendation engine takes into account this transaction history along with other available identities.

So, after an offline purchase where your WhatsApp number was provided, you will receive recommendations tailored to your previous purchase history via WhatsApp.

Following your app purchase, you can expect personalized recommendations delivered through push notifications, email, or other channels specifically centered around the item you purchased.

This approach ensures that recommendations align with customer preferences and behavior, contributing to an engaging shopping journey.

Why are purchase-based recommendations important?

There are several reasons why we recommend using purchase-based recommendations in your omnichannel engagement strategy:

1. Contextual to intent

When you know your customer’s purchase history, you know more about their intent. For example, if a customer has bought a formal outfit, you know their intent of shopping — formal attire in this case. So you have a precise idea of what to recommend to them that matches their intent.

A purchase intent might be different from the interest that a shopper shows when browsing. For example, the shopper might have browsed casual wear, beach wear, and holiday outfits but have settled on buying formal clothes.

Purchased-based recommendations are more contextual to the intent than the interest of the shoppers because purchase shows higher intent vs. the interest shown when browsing.

2. Increase repeat sales

Once a transaction happens, you need to re-engage with the customers to improve the chance of repeat sales.

If you have the purchase data of the customer, you may recommend and prompt with related products through in-app push notifications, WhatsApp messages, or emails.

3. Improve your CLTV

CLTV, or customer lifetime value, is a business metric that measures how much revenue a business can earn from the customer throughout the relationship with the customer.

When the recommendations are made based on the purchase intent of a customer, there are higher chances of converting them into a repeat buyer, which improves the CLTV.

4. Enables hyper-personalization of messages

A personalized message is always good. But why settle for simple personalization like referring to the customer by their “first name” when you can do so much more with purchased-based recommendations?

Using this strategy, Clovia, India’s fastest-growing lingerie brand, saw a whopping 85% uplift in their revenue.

Clovia leverages WebEngage’s funnel feature to understand customer behavior across various channels to analyze drop-offs. They also created a checkout funnel to understand the drop-off of high-intent customers.

Based on these findings, Clovia ran a hyper-personalized multi-channel engagement journey using WebEngage’s Journey Designer to encourage potential customers to complete their purchases.

5. Better upsell and cross-sell opportunities

Say you purchased a pair of denims from the Shoppers Stop app. The next day, you receive a nudge from the brand offering recommendations of tops and tees to pair up with your denim or recommendations for similar denim at a higher price range. Sounds familiar?

Consumers expect brands to remember their prior purchase behavior and spend almost 40% more than planned when they receive hyper-personalized messages.

Knowing prior purchase history and sending product recommendations based on this data can help brands land better upsell and cross-sell opportunities.

6. Boosts AOV

Product recommendation based on past purchases improves upsell and cross-sell opportunities. And when you’re able to cross-sell and upsell to your existing customers, you can improve your average order value (AOV). Here’s how AOV is calculated.

Using this strategy, EGO, the fastest-growing fashion brand from Pakistan, was able to boost its average order value by over 12%.

After analyzing the shopper’s previous purchases on the EGO platform, the team identified their most purchased products. Based on the findings, the team with WebEngage Journey Designer started cross-selling relevant products in a timely manner, increasing their AOV.

What are the types of post-purchase product recommendations you can send?

Here are some examples of different types of post-purchase product recommendations for you to consider.

1. Mode of purchase

For instance, you can send post-purchase recommendations based on their mode of purchase — online or offline. Say the customer bought an apparel through your website. You can send post-purchase recommendations by email and WhatsApp based on the data collected during checkout.

2. Products purchased

Say a customer has purchased a bottomwear. Your post-purchase recommendation can be similar bottom wear at a discounted price or a matching ‘kurta’ or ‘kameez’ to pair with the bottom wear.

3. Product value

Knowing the customer’s previous cart value can hint at their spending power. For example, if a customer previously had a high cart value, it indicates they have decent spending power, and you can recommend them products accordingly.

4. Repeat customer

If a customer is purchasing from you for the second time, it means that the customer has already used your product and trusts you. These users are great prospects to cross-sell/upsell because they’re already familiar with and like the brand.

So, you have a better chance of conversion while up-selling or cross-selling. Look at the CSAT score to determine your satisfied customers and target them with personalized recommendations.

5. Discounts availed

Based on the discounts the customers have availed in their previous purchases, you can cross-sell items available on similar discounts and deals.

6. Based on brand loyalty

Pamper your high-value customers with some special ‘brownies’ in the form of early bird offers, exclusive deals, member-only discounts, etc. When you reward your loyal customers, they feel special and valued. This also subtly encourages them to repeat purchases. Spice it up with relevant product recommendations to shorten their buyer journey.

But how do you make your product recommendations this accurate? This is where a CDP comes into play.

Using CDP for effective post-purchase recommendations

A CDP or a customer data platform is a packaged software that collects customer data from various channels and offers a holistic view of the customer. As there is a dissipation of the third-party cookies along with data influx in our system, brands are leaning on first-party data to gather insights on the customers.

However, the problem arises as there is no way to collect and unify data and orchestrate them for marketing campaigns.

CDP helps brands to collect customer-specific data by integrating multiple channels. This helps in getting a complete 360-degree view of the customer. Once the data is integrated from all the channels, it’s then segregated and segmented for specific marketing campaigns.

Let’s say a shopper has purchased a coord set from the physical store. The same person later buys a watch from the store’s digital app.

The customer has a different journey on multiple channels with multiple intents across the touchpoints.
Sending this customer recommendation based on one touch point can make them irrelevant or complete.

WebEngage’s CDP, for example, ensures that all the customer data is aggregated from various channels for its recommendation engine to send personalized product recommendations.

Going back to our previous example, after the offline purchase, the customer may receive recommendations tailored to clothing via the WhatsApp number that they provided during the store shopping.

Following the in-app purchase, the same customer can get personalized recommendations delivered through push notifications, email, or other channels specifically centered around the item they purchased through the app, the watch in this case.

This omnichannel approach ensures that recommendations align with customer preferences at all stages of the buying journey.

Additionally, the best channel and intelligent sending feature of WebEngage helps marketers make targeting more precise and effective. With WebEngage on your side, you can’t get wrong with precise targeting and sending product recommendations that are apt and timely.

Conclusion

Today, the customer’s journey is not linear, and they have different intent at different touchpoints.

Product recommendations need to adapt and evolve to address the different intents and interests of the customers across various channels where they’re most active.

Journey Designer of WebEngage ties it all together to automate campaigns using an easy-to-use campaign management platform like WebEngage.

Book a free demo today to know more.

In this scenario, Artificial Intelligence (AI) has emerged as a transformative force. Marketing is one of the areas in which AI has the potential to drive immense change, so much so that a study found that along with sales, marketing is the single business function in which AI will have the most significant financial effect.

With its ability to streamline processes, enhance decision-making, and generate more value from marketing efforts, AI can truly revolutionize how marketing strategy can deliver results.
This article will show how AI can effectively leverage your marketing strategy to skyrocket productivity.

The AI Revolution in Marketing

AI plays a fundamental role in today’s marketing landscape. The integration of AI in marketing began with basic task automation and data analysis. The emergence of machine learning techniques has accelerated the adoption and sophistication of how AI can be used in marketing.

Depending on the level of intelligence and whether it is a stand-alone solution or part of a broader framework, marketing AI can be categorized according to two dimensions- less advanced and more advanced, further breaking down into four main types of marketing AI.

As we can see, the range of applications is quite huge. Understanding these quadrants can help marketers choose the applications that serve users’ needs best and design the most effective marketing strategy.

Here are the top 10 ways to leverage AI to achieve 3X productivity.

#1. Predictive Analytics

Predictive analytics is one of AI’s most noteworthy contributions to digital marketing. AI processes huge amounts of historical data by collecting, cleaning, and analyzing it using machine learning algorithms. Thus, it can predict trends, customer behavior, and fluctuations in market conditions. This element of prescience enables marketers to make informed decisions about their campaigns, content strategies, and product launches.

For example, imagine a retail business that sells everything from electronics to groceries. For such a business, managing inventory is a challenge. By cleaning and analyzing the data about sales, consumer behavior, and seasonal economic trends stored in a database, AI can process it.

It can offer insights such as:
“Based on historical data and demand forecasts, we expect a surge in demand for smartphones during the summer holiday season.”
“Our current inventory for stationery products is too high compared to demand. Consider reducing stock and reallocating resources to higher-demand categories.”
“Supplier A consistently delivers orders on time and offers competitive prices. Explore opportunities to expand our partnership with them.”

Thus, based on the analysis, it could suggest inventory optimization, identify the most reliable suppliers, or even suggest a pricing strategy.

Walmart, for example, uses AI to improve daily supply chain workflows, anticipate and work in line with seasonal demand cycles, and even optimize and personalize grocery deliveries.

#2. Customer Segmentation

Customer segmentation can help you target your marketing efforts more precisely, leading to better results. AI can segment your audience with unparalleled accuracy. By analyzing user behavior, demographics, and preferences, AI helps create highly targeted marketing campaigns. This boosts customer engagement and conversion rates, as messages are tailored to individual interests.

Imagine an online fashion retailer that uses AI for customer segmentation to improve its marketing and product recommendations. By analyzing customer data, including purchase history, browsing behavior, and demographics, AI algorithms create distinct customer segments, such as “Frequent Shoppers,” “Fashion Enthusiasts,” and “Casual Shoppers.” The retailer can then personalize the marketing efforts directed at each category. So, a frequent shopper may receive early access to sales events or exclusive discounts, whereas a casual shopper may receive email campaigns highlighting discounts on selected products.

Coca-Cola uses AI for customer segmentation in its marketing campaigns. This allows Coca-Cola to personalize its advertisements, promotional offers, and product recommendations to match its customers’ specific interests and needs based on these segmentations. So, for example, it has different packaging and sizes to appeal to people of varying income levels. Similarly, while it may target a younger audience using advertisements that feature popular celebrities, older patients, who are more likely to be diabetic, may receive promotions for Diet Coke or other healthier product options.

Accurate customer segmentation made the difference for Scripbox, India’s leading digital wealth manager. Initially, Scripbox used segmentation based on demographics such as age. However, they didn’t see the desired results. It was segmentation based on the users’ residence status (domestic vs. NRI) that made a difference. Assisted by WebEngage dashboard features like Send Intelligently,’ ‘A/B testing,’ and personalization opportunities, they were able to leverage communication channels with greater effectiveness. Ultimately, this led to a 3X growth in user engagement, an increase in email open rates, and a reduction in unsubscribe rates.

Explore in-depth how WebEngage can help you achieve precise customer segmentation to deliver the best customer experience.

#3. Chatbots and Virtual Assistants

Chatbots and virtual assistants are the most obvious ways in which customers directly experience the use of AI. They provide 24/7 customer support by answering common queries, assisting with product recommendations, and guiding users through the sales funnel.
Imagine a customer who visits the website of a bank or insurance company, looking for a specific financial product. Presented with a wide range of choices on the website, the customer may want immediate guidance on which product best fits their financial goals. At this point, a chatbot can assist the customer to choose by responding to questions. It can also utilize the interaction with the customer to upsell another product.

Airbnb, for example, employs a chatbot on its website to help users with various tasks such as finding and booking accommodations, customer support during the booking process, and getting refunds. This has allowed Airbnb to enhance the host and guest experience.

#4. Content Generation

Generative AI-powered content generation tools can help create blog articles based on trending keywords, social media posts with relevant hashtags and captions, and even video scripts for product demonstrations or promotional videos. While these tools are not capable of completely replacing human creativity, they can help marketers save time and maintain a consistent content schedule.

Generative AI can be used in unique ways to engage customers and get them to participate in innovative marketing campaigns. A brilliant example of a company that does this well is Coca-Cola. Most recently, it has generated a buzz around its latest “mystery” flavor, Coca-Cola Y3000, which it says was co-created with AI. Similarly, the ‘Create Real Magic‘ campaign helped Coca-Cola encourage talented creators and artists to work with Generative AI to develop unique and attractive images featuring Coca-Cola assets. These images were featured on billboards in prime locations like New York’s Times Square.

#5. Content Optimization

In a world of search engines that rank content based on multiple factors, it is necessary to create quality content and optimize it so potential customers can easily find it. AI-driven SEO tools assist marketers in identifying keywords, tracking rankings, and analyzing competitors. They can also provide recommendations for optimizing on-page content and structure, which enhances organic search visibility. Thus, AI allows businesses to keep up with evolving search engine algorithms and user behaviors, ultimately refining their online visibility and search engine rankings.

Zillow, a leading online real estate marketplace, implemented AI-driven content optimization strategies to improve its search engine rankings and user engagement. Aside from recommendations about keywords, user behavior analysis, and dynamic content generation, AI also helped Zillow improve its local SEO efforts by analyzing location-based search queries. As a result, Zillow saw a noticeable increase in website traffic and improved engagement metrics as their listing began to rank higher.

#6. Email Marketing Optimization

Email marketing is a must-have in any marketer’s toolbox. AI can improve email marketing by analyzing subscriber behavior and delivering personalized content and recommendations, leading to higher open rates, click-through rates, and conversions. AI can also optimize and automate send times and subject lines to maximize engagement.

Expedia, a leading online travel agency, aimed to boost its marketing performance by crafting more persuasive and engaging email subject lines. Using AI, they discovered emotional and linguistic patterns that resonate with specific customer segments. This led to an uptick in click-through rates and revenue generated from email marketing.

Juicy Chemistry, a D2C brand offering natural and organic skin products, achieved 4.5X growth in email conversions and 2X improvement in email open rates. They could do this by using fewer yet more sharply targeted communications, along with optimization of channels, segments, and spending, using detailed analytics from WebEngage.

Unlock the potential of your email marketing strategy with WebEngage’s expert assistance. Dive deeper into your possibilities.

#7. Programmatic Advertising

Programmatic advertising platforms leverage AI to automate ad buying and placement in real time. AI can optimize your bidding strategy, generate and deliver personalized ads, and help you understand your audience better. This ensures your ads reach the right audience. This makes ad campaigns more effective and efficient.

Amazon, for example, uses AI algorithms that analyze customer data and behavior, including past purchases, to optimize ad placements on its e-commerce platform.

#8. A/B Testing and Optimization

A/B testing identifies winning variations and suggests product, service, UI, and UX improvements. AI accelerates and enhances A/B testing by automating processes, conducting complex statistical analyses, and enabling personalization and dynamic content testing. This allows marketers to optimize landing pages, ad copy, and other elements of their digital marketing strategies for better results.

Imagine that a travel booking website wants to test the impact of using different images in email marketing campaigns. In AI-driven A/B testing, users are served automatically selected images based on their preferences and past interactions with the website. This allows for greater personalization, as users receive emails with images they will most likely connect with. Airbnb, for example, has successfully used AI for A/B testing.

Closer to home, for Bajaj Finserv EMI Store, using WebEngage’s Send Winner of A/B Testing Automatically feature allowed them to test different variations of their campaigns and then send the best one to their audience. Thus, implementing A/B test insights in real-time was a crucial factor that helped them to run more effective campaigns. This, in turn, led to an increase in user engagement, 3.5 X increases in conversions, and a 17% increase in conversions from retargeting efforts.

#9. Social Media Management

Most successful brands use social media today. AI tools can study social media conversations and trends to help you design your content strategy. AI can also automate posting schedules and monitor brand mentions, allowing for more effective social media management and engagement. AI-driven sentiment analysis tools can monitor social media mentions and comments to gauge audience sentiment. This can help you understand how your customer perceives your brands and products. This, in turn, will enable you to adjust strategies accordingly.

AI can also help with influencer marketing. Using natural language processing tools, for example, AI can predict how well an influencer’s style and voice will align with the brand’s goals. Accordingly, brands can select the social media influencers whose content resonates the most with the brand.

Coca-Cola relies heavily on AI for its marketing efforts, including social media marketing. In Japan, the company’s AI-powered app, Coke On, allows users to access a loyalty scheme by buying a drink from a vending machine. Innovative efforts like these enhance customer engagement and brand loyalty.

#10. Customer Relationship Management (CRM)

AI-powered CRMs enable businesses to manage customer data effectively. They can track interactions, analyze customer sentiment, and even predict when a customer might be ready to purchase. Additionally, AI can reduce customer “churn” by identifying leak patterns in conversion funnels. Overall, AI-driven CRM can help build stronger, more personalized customer relationships.

Coca-Cola is a prime example. They implemented an AI-powered CRM system that enabled them to track customer behavior and preferences. They later leveraged this data to design targeted marketing campaigns. The system also helped them identify improvement areas for their customer service function.

The Future of AI in Marketing

As per research, the AI market is poised to grow twentyfold by 2030. Around 97 million people are expected to work in AI by 2025.

This shows that AI is here to stay. Emerging AI trends like AI-driven voice search optimization and augmented reality marketing will continue to shape the digital landscape and radically transform how brands engage with buyers.

As AI technology advances, businesses that embrace these trends can stay ahead of the curve in optimizing their marketing strategy.

Conclusion

AI is not just a buzzword but a powerful tool. Businesses that embrace AI-driven marketing strategies will find themselves better prepared to respond to changes in the digital marketing arena. AI can help you increase productivity, make data-driven decisions, and offer personalized experiences to your tech-savvy consumers.

WebEngage is well-positioned to help you with your AI technology needs. Request A Demo to explore what WebEngage can do to help you harness the transformative power of AI.

With a mobile-first audience in 2024, it’s not just about sending messages; it’s about sending them at the right time, in the right sequence, and ensuring that each interaction adds value to the user experience.

App personalization has emerged as a game-changer, allowing businesses to tailor their user experiences and engage with their audience on a more intimate level.

As part of our ongoing commitment to providing you with the best app personalization stack, WebEngage is excited to introduce 2 new features:

Together, they amplify your ability to craft personalized, effective, and adaptive user experiences.

Let’s delve into both of these concepts individually:

Campaign Prioritization

The Challenge of Campaign Overlaps

Have you ever found yourself in a situation where multiple campaigns overlap, targeting the same sets of users? It’s a common dilemma faced by marketers seeking to optimize their outreach efforts. The question arises: How can you determine which campaign takes precedence and is sent to the user first?

Decoding Campaign Prioritization

Enter WebEngage’s Campaign Prioritization – a solution designed to empower businesses with the ability to decide the order in which their campaigns are delivered to users. This innovative tool allows marketers to take control of their campaign strategy, ensuring a seamless and personalized experience for their audience.

How it Works

Campaign Prioritization provides a user-friendly interface where you can effortlessly assign priority levels to your campaigns. This functionality allows you to set the order in which campaigns are presented to users, ensuring that the most relevant and impactful messages take precedence.

Moreover, if a user qualifies for multiple campaigns, he will be shown first the one that is prioritized. While by default, journey campaigns are given higher priority, with this feature, you can prioritize a standalone campaign.

Why Do You Need It?

Optimizing User Engagement: By strategically ordering your campaigns, you can optimize user engagement and increase the chances of capturing their attention with the most compelling messages. This feature empowers you to enhance the overall effectiveness of your marketing efforts.

Campaign Lifecycle

We have added additional controls to our app personalization channels, i.e., in-app and in-line content, that will allow users to define campaign view limits, recur campaigns, etc.

The feature of strategic recurring campaigns is one with much potential, allowing marketers to reintroduce successful campaigns at intervals that resonate with their audience, maintaining interest and relevance over time.

This is an enhancement to our earlier ‘Max limit’ option. Configuring this Campaign Lifecycle allows clients to specify how many times a specific campaign should be displayed to a user and whether it should be repeated/recurred.

Here is what it looks like on the dashboard:

PS. The blue boxes underneath the campaigns help you decode exactly how long you’ve scheduled your communication for. Use them as your little helpers!

Why Do You Need It?

1. Preventing Campaign Fatigue: Define view limits to ensure users are not overwhelmed by repetitive messages, enhancing the overall user experience and avoiding potential disengagement.
2. Strategic Recurrence Patterns: Empower marketers to reintroduce successful campaigns at specified intervals, maintaining user interest and relevance over time.
3. Adaptability to Changing Dynamics: Businesses gain the agility to adapt to evolving marketing landscapes by finely tuning the lifecycle of their campaigns and responding to shifting user preferences and industry trends.

How it Works

1. The client can set how many times a notification will be viewed until it’s clicked once (similar to our existing ‘max limit’ option).
2. If the client wants to recur this notification, then they can tick the checkbox.
3. Once checked, the following needs to be configured:
   • Frequency: Define the frequency limit – Hourly, Daily, Weekly, Monthly
   • The number of recurring cycles: Define how many times the cycle will be repeated. Either it can be set to a finite value or until the campaign ends.

To learn more: Watch our video here.

How is it different for in-app and in-line?

Simple.
For in-line, there’s a view limit.
This means you can limit how many times a user will view the campaign.
For in-app, if your user clicks on the notification once, it can be dismissed.

To summarize, with Campaign Lifecycle, you can define a cycle (how many times a campaign is to be shown until it’s clicked once), the frequency of repeating the cycle (daily, weekly, etc.), and the number of times the cycle will be repeated.
To understand further, refer the in-app Knowledge Base document (Knowledge Base for app in-line will be updated soon).

Please note:

1. For in-line campaigns, only the number of views is taken into consideration (unlike in-app, wherein clicks are also considered).
2. This feature would require core SDK updates: Android v4.6.0 and iOS v6.5.0.

Use cases:

Here are some use cases for your business that you can implement using Campaign Lifecycle:

E-Commerce:

Time-Bound Festive Coupons: Enable a weekly/daily nudge to incentivize users to make a purchase on the platform. Fetch user data or personalized discount coupons through the Catalog for an added level of customization for your users.
Suggested channel: In-app personalization

Edtech:

Course Reminders and Updates: Show periodic reminders about upcoming classes, assignment due dates, and important updates to students. This ensures continuous engagement and keeps learners informed throughout the duration of a course.
Suggested channel: In-app personalization

Travel & Hospitality

Rewards & Gamification: Implement Campaign Lifecycle to nudge users to collect rewards to purchase on the platform with gamification. With elements like scratch cards, spin the wheel, points, and more, create a holistic experience that keeps users engaged and retained.
Suggested channel: In-app personalization

BFSI

Insurance premium reminders: Remind users to pay the upcoming months’ premiums. For unknown users or users on the platform who haven’t converted into paying customers, implement the feature to sign up and transact on the platform.
Suggested channel: In-line personalization

Frequency Capping for In-App Notifications

We’re bringing you frequency capping within in-app notifications.

What does it mean?
Frequency Capping helps you control the number of views per session. This means you can control how many in-app notifications can be seen by a user within a session.

When enabled, this setting ensures a thoughtful and non-intrusive user experience by preventing back-to-back notifications when a user qualifies for multiple messages.

How it Works

Frequency Capping allows you to specify the time interval between displaying multiple notifications to a user. If enabled, this setting prevents two campaign notifications from being displayed back to back if a user has qualified for multiple notifications.

PRO TIP: You can also combine campaign prioritization and campaign lifecycle. Have fun experimenting with these!

Conclusion: Why Campaign Lifecycle should matter to you

The introduction of WebEngage’s Campaign Prioritization and Campaign Lifecycle features marks a significant stride toward a more personalized and effective approach.

Campaign Prioritization puts control firmly in the hands of marketers, allowing them to decide the order in which campaigns are presented to users. This not only ensures the most impactful messages take precedence but also adds a layer of customization that resonates with users on a more individual level.

Simultaneously, the Campaign Lifecycle feature provides a nuanced and adaptive approach to campaign management. With the ability to define view limits, recur campaigns, and implement frequency capping within in-app notifications, businesses can now navigate the delicate balance between visibility and moderation.

With Campaign Prioritization and Campaign Lifecycle, the future of marketing is not just about reaching users; it’s about reaching them with the right message, at the right time, and in a way that truly resonates.

Embrace the power of control, tailor your strategies, and unlock the full potential of personalized user engagement with WebEngage’s latest innovations.

For more information, check out the Knowledge Base here.
Get in touch with your Customer Success Manager or reach out to us at product@webengage.com.

Pernia’s Pop-Up Shop, India’s largest luxury fashion e-commerce platform owned by Purple Style Labs (PSL), is home to the finest selects in luxury fashion & lifestyle. Bringing together India’s most-coveted labels, the multi-designer destination is the most sought-after space for bridal and occasion wear, offering an exquisite curation of designer womenswear, menswear, jewelry, home decor, kidswear, and more.

The brand’s impact extends beyond being an online marketplace; it plays a pivotal role in promoting and supporting Indian designers as well as the Indian fashion industry.

Pernia’s and WebEngage – A collaborative effort

Company’s Objectives:

1. Data Cohesion and CDP integration: The objective extends to bringing data together cohesively, facilitating a unified view that transcends fragmented sources and provides a holistic perspective on customer behavior and preferences.
2. User Behavior Tracking: Pernia’s Pop-Up Shop aspired to meticulously track user behavior, going beyond transactional insights to grasp the nuanced choices and evolving preferences of its diverse customer base.

Company’s challenges in driving the objective

1. Increased Data Silos: Operating across multiple platforms introduced complexities to the e-commerce platform, resulting in the creation of data silos.
2. Lack of Personalized Communications: Achieving personalized communications posed another challenge, given the diverse and unique tastes within the realm of fashion. The brand strived to tailor messages effectively to resonate with individual preferences.

In addressing these challenges, Pernia’s Pop-Up Shop recognized the need for strategic collaboration. Turning to WebEngage, the partnership sought innovative solutions to navigate the complexities of data integration, break down silos, and enhance the personalization of communications. 

Why Did Pernia’s Pop-Up Shop Pick WebEngage?

Before onboarding WebEngage, the e-commerce brand used different platforms for different channels – this was not only more manual work but also slowed the team down holistically by having their data on multiple platforms.

That is where WebEngage stepped in.

By using only 1 platform to collate and gather all their user data, Pernia’s Pop-Up Shop was able to automate most of their manual labor and enable a smoother user experience journey. 

Result: What did the e-commerce brand achieve?

Global mobile phone users were estimated to be 6.8 billion in 2023 and will only grow from here. This is why ensuring the highest level of personalization is imperative.

It not only gives you an edge over your competitors but also is a way to skyrocket your revenue. It’s the difference between a generic experience and a personalized one, where users feel seen, understood, and valued.

Introducing WebEngage’s App Personalization

Divided into in-line and in-app personalization, WebEngage provides a holistic way to contextualize messages that increase engagement and drive revenue. Backed by real-time user insights and powerful features, you are bound to create memorable experiences for your users each time!

What features does WebEngage’s App Personalization have? How can you use them? What are the benefits? This blog will answer all for you.

Why You Need App Personalization:

The need for app personalization stems from the evolving expectations of today’s users. In an era where attention spans are limited, and choices are abundant, delivering generic experiences may result in users quickly losing interest or abandoning an app altogether. Here are key reasons why app personalization is essential:

• Enhanced User Engagement: Personalized experiences capture and maintain user attention by showcasing content and features that are specifically relevant to them. This not only increases the time users spend within the app but also fosters a deeper connection with the brand.
• Improved User Retention: Users are likelier to stick around when they feel an app understands their preferences and caters to their needs. Personalization reduces churn rates and increases each user’s lifetime value.
• Increased Conversions: Whether it’s making a purchase, signing up for a subscription, or completing a specific action within the app, personalized experiences can significantly impact conversion rates. Businesses can drive desired actions and achieve their goals by offering users tailored recommendations and incentives.

1. What is the difference between In-App and In-Line?

In-App:
In-app personalization is centered around tailoring content either as pop-ups or within-the-app elements that can be dismissed post-action taken by the user or after a specific time.
For Instance: For a travel app using WebEngage, you can showcase personalized pop-ups suggesting upcoming beach destinations that align with the user’s past travel choices.

In-Line:
In-line personalization focuses on customizing content and elements directly within the user interface or the app screen.
For Instance: An e-commerce app leveraging WebEngage can implement in-line personalization to send targeted communication during flash sales or promotional events.

2. What does the difference look like?

Breaking down In-App Personalization

At WebEngage, we have made it easy for you to personalize all your campaigns by leveraging real-time data points related to your user’s preferences and behavior. These data points are referred to as User Attributes and Events, respectively, and make it possible for you to deliver tailored experiences at scale.

Thus, the first step is to get all these User Attributes and Events flowing into your WebEngage account from your app. Learn more about setting up campaigns here.

WebEngage Features: WebEngage allows businesses to dynamically adjust the app’s interface, content, and features, in-app messages and pop-ups delivered based on user preferences and behaviors.

Layout options for in-app:

Use cases for your business using in-app personalization:

1. Feedback and survey: (For Travel/OTA/Hospitality)
• Target Audience: Users who’ve completed a stay or booked a trip with the app.
• Brief: Nudge users within the app to provide feedback & reviews to further improve user experience. Personalize follow-ups based on booking & travel experience.
• Impact: Gather user data to measure NPS, provide loyalty benefits, discount coupons and more.



2. Dynamic In-Game Challenges: (For Gaming)
• Target Audience: Users who actively engage in the app.
• Brief: Deliver a personalized gaming experience that evolves with each player’s unique journey. Design personalized challenges, adjusting difficulty levels, rewards, and objectives based on the user’s gaming history, skill level, and preferences.
• Impact: An immersive gaming experience that drives user loyalty.



3. Medication Reminders and Education: (For Healthcare)
   • Target Audience: Users with specific prescription needs or seeking health education.
   • Brief: Send medication reminders tailored to the user’s prescription schedule. Integrate educational content about medications, potential side effects, and lifestyle tips personalized to the user’s health condition and medical history.
   • Impact: Increased user trust in the healthcare app, leading to user satisfaction.

Breaking down In-Line Personalization

In-line personalization allows you to create display ads that will look native to the app and run personalized campaigns on the app to help achieve their use cases without hindering the end user’s experience.
WebEngage Features: The advantages of WebEngage’s app in-line personalization are that you can update creatives without sending an app update, dynamically update home page cards, cross-sell/upsell with products, send carousel campaigns, and enable geolocation personalization as well.

Layout options for in-line:

• Text Layout:


Developers can leverage a card structure focused on textual content. This format supports basic styling, including buttons and icons for enhanced interactivity.

• Banner Layout:


For a more visually engaging experience, developers can opt for a card layout enriched with images. This banner option supports basic styling and allows the integration of buttons

• Custom View Layout:


The custom view layout option provides the utmost flexibility, allowing you to create your own layouts, and enabling you to explore your creativity as much as possible, while WebEngage provides you with personalized data.

Please note: There will be an option to edit layouts. Users can also add multiple layout variations—contact product@webengage.com for any further layout options you might want to explore.

Use cases for your business using in-line personalization:

1. Personalized Shopping Cart Discounts: (For E-Commerce)
   • Target Audience: Users with items in their shopping carts.
   • Brief: Dynamically present personalized shopping cart discounts at the checkout stage. Employ on-page elements or banners to showcase exclusive offers tailored to the user’s past purchases, encouraging swift and satisfying transaction completion.
   • Impact: A frictionless user experience and better conversion rates.

   

2. Personalized Investment Portfolios: (For BFSI/Fintech)
   • Target Audience: Users engaging in financial activities on the app.
   • Brief: Deliver user-specific investment portfolio recommendations through the app interface that seamlessly adjusts to the user’s risk tolerance, financial goals, and investment history. This empowers the user to make more informed investment choices.
   • Impact: Informed decision-making, elevating customer satisfaction

   

3. Course Recommendations Based on Learning Style: (For edtech)
   • Target Audience: All users
   • Brief: Integrate in-line personalization to recommend courses based on individual learning styles. Utilize banners or other on-page elements to suggest courses aligned with the user’s learning preferences.
   • Impact: Improved user interactions and learning outcomes.

Statistics you must track using WebEngage’s App Personalization:

1. Clicks on Cards and Buttons:

Track clicks on visually enriched card elements and actionable buttons to evaluate user engagement with different interactive elements within the app.

2. Conversions:

Monitor instances of user conversions, such as purchases or sign-ups, to understand the effectiveness of conversion strategies and user behavior.

3. Revenue from User Interactions:

Measure revenue explicitly generated from user interactions, including card and button clicks, tying engagement efforts directly to financial outcomes.

4. Clicks on Engagements:

Evaluate the overall engagement level by tracking the total number of clicks on various interactive elements within the app, providing insights into popular features.

5. Impressions (Including Default Content Views):

Assess impressions of content views, including default views presented to users, for a comprehensive understanding of user engagement with personalized and default content.

Conclusion

Today, standing out and fostering lasting connections with users is paramount.
By integrating app personalization strategies, businesses unlock the door to unparalleled user engagement, increased conversions, and, ultimately, sustainable revenue growth.
Take the leap into the future of your app personalization with WebEngage. Book a demo with our experts to witness the full potential of app personalization.
Your personalized app experience awaits – let’s create it, refine it, and make it uniquely yours.

From music to marketing, we can’t go on without reflecting on the year that was. So here we are – with our version of the most compelling marketing trends of the year and how WebEngage played a role in it.

At the start of 2023, words like purpose-led marketing, omnichannel, voice search, authenticity in the content, personalization, privacy, and platform governed the talks. Then, one day, AI knocked on the door.

Without further ado, let’s get into it.

1. The introduction of Generative AI

From content creation to content curation, chatbots to personalization, and predictive analysis to segmentation, AI pitched in everywhere, leaving marketers wanting more. 85% of marketers are already updating their skills because of AI, reports marketing data state of play.

Brands use AI to build content calendars, write blogs, copy ads, and more. Here is a detailed account of Plum using AI to write blogs at scale.

AI-generated text, exemplified by tools like GPT-4, and AI-generated images, led by technologies like DALL-E and Midjourney, brought new-age creativity to the table.

Then, of course, AI was used for audio generation, text-to-speech projects, predictive analytics, segmentation, lead scoring, and overall campaign management.

2. Hyper-personalization

A McKinsey study revealed that 76% of users are likelier to buy from brands that personalize. This year, brands went berserk with personalization from web to mobile and across omnichannel communication.

With big data in motion, customers do not want to go back to general, non-personalized recommendations across all touchpoints. As a result, brands are spending a lot on increasing their overall engine.

Collectively, the marketing fraternity deduced that the reward for delivering this would intensify their loyalty and retention, reduce churn, increase engagement, and contribute to overall growth.

Oral Care Brand Perfora Witnesses An 8X Spike In Conversions With Personalization

3. Consumer Privacy

One may wonder how privacy and personalization go hand in hand. It’s not like customers do not see the benefit of using data to offer personalized offers, deals, recommendations, and solutions, but at what cost?

85% of global adults want to do more to protect their online privacy. Use the data; don’t misuse, misguide, or breach any trust. Do not sell the data or collaborate with 3rd party vendors your customer didn’t sign up for.

Nearly all reputable organizations are changing ways of communication to build trust with customers, ensuring their data is safe. This communication allows customers to sign up for emails, pushes, SMS, or any marketing activity without apprehension.

In addition, regulatory bodies are invested in how marketers use their data, as evidenced by the Digital Personal Data Protection (DPDP) Act in India, the General Data Protection Regulation (GDPR) in Europe, and the California Consumer Privacy Act (CCPA) in the United States. Compliance protocols like Service Organization Control Type 2 (SOC2) are already being enforced across organizations.

4. Prioritizing social presence

Both millennials and GenZ are too busy to opt for traditional routes to seek assistance. So your brand has a chat, email, SMS, and call as a service, but where do most complaints go?

Social media, especially Twitter. Brands that ghost users online and don’t offer solutions take the heat in multiple ways. This type of marketing includes having a dedicated ORM team on social media to address customer queries.

5. VR-based apps and tools

Unless you’ve been living under a rock, you know VR is taking over the advertising world. AR and VR are touted to boost the world economy by a whopping $1.5 trillion by 2030.

Many brands have now begun their augmented reality projects. Ikea recently built a VR showroom, Sephora launched a Virtual Artist app, and Lenskart allows you to wear eyewear using AR. Amongst the ones that went viral was Maybelline, as shown in the image below, using CGI techniques to create an artistic OOH.

In 2023, we saw decent AR and VR technologies adoption by brands across sectors to draw user attention and we can’t wait to see what 2024 has in store.

6. Working with the influencers

Influencer marketing is yet to reach the top of its bell curve. A trend that picked considerably around 2020 is still drawing in millions. This year, we saw a massive uptick in the adoption of micro and nano influencers (due to high engagement rates).

70% of Indians believe influencer marketing impacts them – making brands even more confident with each passing day.

Brands are also becoming more prudent with their selection, navigating through the challenges quoted by demographics, engagement rates, reach, relevancy, activity, tone of voice, and overall persona.

7. Experiential marketing made a comeback

In the 1990s, brands loved to engage a live audience, record the reaction, and publish it for the masses. This trend was seen in video, movies, radio, and print ads. With every brand in the queue, it had hit its peak, but apparently, it’s making a comeback.

2023 saw brands trying out experiential marketing in many ways. Here’s a recent example from Netflix India. To launch the movie Archies, Netflix bought a digital billboard that changed daily with the number of days left for the movie to go live.

Result? It’s a resounding hit on social media.

Marketing through the lens of WebEngage

WebEngage has supported numerous brands in these endeavors, from sending out timely communication to crafting personalized campaigns that hit the spot.

Please take a quick look with us.

Event volumes – 1.2 Trillion

In 2023, WebEngage witnessed a staggering 1.2 Trillion events on its platform, showcasing immense user activity and engagement.

Monthly Users Engaged – 1.2 Billion

By unlocking a little over 800+ global clients in reaching their customers on time via app and web, WebEngage addressed a mammoth volume of 1.2 Billion monthly users in 2023.

The platform indicated a widespread, tactful reach with impressive delivery rates by handling traction of such a high volume.

Industries covered – 15+

From BFSI to healthtech, D2C to e-commerce, travel & hospitality, and telecom, in 2023, the services spanned 15+ industries, showcasing versatility and adaptability across sectors.

Messages sent monthly- 42.8 Billion

Every month, the team at WebEngage facilitated messages sent via their systems to a mammoth volume of 42.8 billion – that’s like touching the entire world’s population 5 times.

Crazy.

Total Sent Volume – 465 Billion

A remarkable feat was achieved by sending 465 billion messages through 2023. These messages spanned from welcome pushes to onboarding nudges, from offers to deals, underlining the platform’s integral role in shaping brand communication.

Channel-wise sent volumes

• App Push –WebEngage delivered a promising 236 Billion app push notifications showcasing the relevance of mobile app engagement
• Web Push –The platform also sent out 198 Billion web pushes, highlighting the growing significance of web-based communication
• Email –Together for all its brands, a whopping 20.7 Billion emails were sent out in 2023, emphasizing that emails are still one of the most potent branded communication tools.

Channel-wise conversion numbers

• Email –With email, an astounding conversion rate of 13.17% was achieved, attesting to the effectiveness of the channel
• In-App –Another promising marketing lever, in-app pushes, showed a notable conversion of 10.14%, presenting itself as a critical driver for user action within the app.
• Web Personalization – Overall, as personalization ruled the year, with WebEngage, the efforts saw a conversion of 4.49%, demonstrating the success of the tailored experience.

Whether you’re managing an app or a website’s product owner, WebEngage will support you in your many marketing endeavors. With its extensive marketing automation suites and solid experience across various sectors, the platform has been state-of-the-art for running cutting-edge marketing campaigns.

Our Predictions for 2024

In 2024, the marketing landscape is poised for notable shifts. We’re sure that AI will get more significant than what it is now and slowly make its way into enabling real-time highly tailored campaigns.

Furthermore, sustainability, social responsibility, and showing up for the right cause will become strategic initiatives that most brands will lean over. The current audience is sensitive, quick to judge, and build impressions. Brands need to be on edge to maintain a strong brand voice.

Video content will continue to dominate. However, it will be shorter than it has ever been. Be prepared to have interactive formats and engagement during the stream.

The need to automate content will rise again – with each social media platform demanding its unique content style, repurposing, automation, and diversification will become the need of the hour. This is where generative AI will step in.

All in all, we marketers must be on our toes to do edgy stuff all the time. However, you don’t have to do it alone. We specialize in handholding our customers through evolving trends as preferences change and sentiments rise and fall. If you’re even a tiny bit curious to take a sneak peek at what we’re all about, book a free demo.

On that note, we wish you a happy and prosperous new year.

What is Loyalty?

The traditional concept of customer loyalty in retail revolves around customers consistently choosing a particular retailer’s products or services over its competitors. However, loyalty today is no longer just about repeat customers or the frequency of purchases. With leaps in technology, loyalty in fashion retail has become a factor in customer retention and a vehicle for designing personalized and memorable experiences.

Modern engagement programs focus on personalization, experiential rewards, omnichannel approaches, community building, and establishing emotional customer connections. Omnichannel approaches integrate various customer interaction channels for seamless experiences. These engagement programs have several benefits, including enhanced customer retention, positive word-of-mouth, competitive differentiation, and increased customer data insights.

Maximizing Loyalty

Here are some best practices to maintain a high Customer Lifetime Value with loyalty exercises:

• Send relevant and transparent messaging: Customers are driven to purchase items when the messaging reaching them is accurate and has a high level of personalization. WebEngage partnered with India Circus to boost Its Click-Through Revenue By 23% with web personalization and using the Journeys feature.
• Deliver a personal touch: Go the extra mile to show that your customers matter to you. Experiences curated on big occasions in your customer’s life personally addressed letters, and gift bags are some surefire ways to increase customer engagement.
• Reward customers for their loyalty: Treat your most loyal customers with loyalty exercises that make them feel special. Rewards and discounts, whether in a points-based or tier-based program give the customer a sense of belonging and appreciation.
• Offering expert advice through social media: Use your social media properties as true extensions of your loyalty exercises. With useful and informative content, you can alter the customer experience from transactional to emotional.

II. Use cases to implement personalized loyalty programs

A. Customization Based on Customer Lifetime Value

With WebEngage’s Customer Data Platform, get customer insights at your fingertips and monitor the effectiveness of your loyalty programs. To know how we helped Amyra, a clothing brand, achieve 5x growth in revenue, go here.

Use Case 1: How H&M is gaining high CLV with its unique Loyalty efforts

H&M’s loyalty program, designed to foster long-term relationships with customers, has successfully amassed over 100 million members globally. The structure of the H&M loyalty program is tiered, offering escalating benefits as customers reach higher spending thresholds. Members become Plus members upon earning 500 points, which is equivalent to $500 in purchases. This premium tier grants additional perks like free shipping and returns, unique experiences, and access to limited collections. A key feature of the program is its sustainability angle, where members are encouraged to recycle clothing in exchange for coupons, aligning with the company’s broader sustainability efforts​​.

B. The Role of Intelligence in Loyalty Programs

Many fashion brands today have joined the AI bandwagon to personalize their loyalty content. With automated marketing tools, backed by AI, WebEngage can address your retention worries and create hyperpersonalized marketing campaigns to keep your customers devoted to your brand.

Use Case 2: Explore how Zara utilizes artificial intelligence to recommend products aligning with individual customer styles

Zara has integrated artificial intelligence (AI) into its operations to enhance efficiency, responsiveness, and customer engagement. For customer engagement, Zara has implemented AI to predict customer behavior based on attributes like size, color, fit, and style. This predictive capability is part of Zara’s collaboration with technology partners, where it utilizes microchips in clothing tags for enhanced inventory visibility and sophisticated logistics systems for optimized transportation and inventory management.

C. Curated Experiences for Enhanced Customer Engagement

To create a deeper connection with your customers that goes beyond mere transactional benefits, it is important to design innovative ways to connect to them via loyalty programs, offers and discounts, personalized messaging, and so on. WebEngage provides advanced customer retention tools that automate the flow of messaging content with omnichannel distribution. A case in point is how WebEngage introduced marketing automation to Man’s fashion brand Powerlook and achieved a 302% uptick in unique conversions.

Use Case 3: How Stitch Fix provides personalized style recommendations based on customer quizzes and feedback

Stitch Fix offers a unique approach to personal styling, enhancing customer engagement through a blend of data science and human intuition. Customers begin their journey with a detailed questionnaire covering aspects like lifestyle, body type, and preferred items. This data feeds into Stitch Fix’s algorithm, helping it better understand customer preferences based on various factors, including age and location. The ‘Style Shuffle’ feature further allows the company to amass vast amounts of data, acting as a ‘Tinder for clothing’ where users swipe on outfits they like or dislike.

D. Building Stronger Connections through Personalization

Customers appreciate it when you take the effort to contextualize messages to their tastes and preferences. A large part of earning and retaining loyalty comes from well-executed engagement strategies that make the customer feel wanted. WebEngage’s personalization capacities are backed by AI-led content gathering and analyzing, along with marketing automation tools that help tailor the perfect message and deliver it through the apt channel.

Use Case 4: How Simply Be used UGC to personalize customer rewards

Simply Be, a fashion retailer, innovatively leveraged User-Generated Content (UGC) to personalize customer rewards, fostering a more engaging and tailored shopping experience. By encouraging customers to share their fashion choices and experiences on social media with specific hashtags, Simply Be was able to gather a wealth of real-world images and reviews of their products.

First, they featured customer photos in their marketing materials, both online and in-store, providing a realistic representation of how their products look on a diverse range of body types. Customers whose photos were selected received special discounts or loyalty points, incentivizing participation. Furthermore, Simply Be analyzed the UGC to understand customer preferences and trends better, which enabled them to offer personalized product recommendations and rewards that resonated with individual customer styles.

Case Study: Sephora Beauty Insider – Sephora’s engaging retention platform

Sephora significantly amplified customer engagement and scaled its business through the strategic use of its loyalty program, Sephora Beauty Insider. This program was ingeniously designed to offer a tiered system – Beauty Insider, VIB, and Rouge – each providing escalating rewards and exclusive benefits, thus incentivizing increased spending and loyalty. Members earned points for every purchase, which could be redeemed for a variety of rewards, including exclusive products, special events, and personalized beauty experiences.

Crucially, Sephora integrated personalized beauty recommendations and services within the program, leveraging customer data to offer tailored product suggestions and makeup advice. Additionally, the Beauty Insider program included unique features like birthday gifts, early access to new products, and members-only events, which fostered a sense of exclusivity and community among participants.

WebEngage can make your personalized marketing campaigns a breeze. While the unified data platform functions as a receptacle of information from various customer sources, the marketing automation tools power engagement and loyalty campaigns with ease.

E. How Personalization Influences Purchase Decisions

Personalized and tailored messaging has a powerful effect on consumer purchase decisions. WebEngage’s Journey Designer automates the flow of marketing campaigns that are contextual and personalized, accruing high ROI on ad spend.

Use Case 5: How ASOS tailors promotions to individual shopping behaviors, leading to higher average order values

ASOS, a British online fashion and cosmetic retailer, has effectively utilized personalized promotions to influence purchase decisions and increase average order values. Leveraging a data-driven approach, ASOS has created a highly personalized shopping experience for its 23 million active users. The company uses a recommendation tool powered by cognitive analytics, matching customers with experiences that promote maximum engagement and drive desired outcomes. This tool tracks individual behavior in real-time, allowing for scalable recommendations.

Additionally, ASOS’s visual search feature uses machine vision to suggest relevant items based on scanned clothing, further enhancing personalization. These strategies have contributed to ASOS’s significant revenue growth and customer engagement, with improved metrics like units per basket and conversion rates.

III. Challenges and Solutions

Use Case 6: How H&M addressed customer data privacy concerns when implementing personalized loyalty initiatives

H&M, while implementing its personalized loyalty initiatives, H&M has faced the challenge of addressing customer data privacy concerns. To overcome this, the company has made a strong commitment to protecting personal data and ensuring customer privacy. They provide clear and transparent information about the personal data they collect, including the purpose and usage of this data. H&M processes personal data to enhance the customer experience, both online and in-store, and for fulfilling service requests such as order deliveries and customer support.

Use Case 7: How Nordstorm maintains a balance between personalization and maintaining a positive overall consumer experience

The retailer has successfully integrated online and in-store commerce, ensuring a seamless and user-friendly experience. This approach is evident in the way Nordstrom has adapted its brick-and-mortar stores to support the e-commerce experience without relegating them to mere fulfillment centers.

Key to Nordstrom’s balance is its strong connected loyalty program and optimized sales floors for services like click-and-collect. The company provides detailed information on product pages, including delivery and pickup windows and the number of people viewing the same item, helping shoppers understand potential delays for popular items. In-store, Nordstrom enhances the shopping experience by placing pickup counters at the front of the store, maximizing convenience for online shoppers without disrupting the in-store browsing experience.

Such omnichannel experiences can be easily streamlined using retention marketing tools by WebEngage.

VII. Conclusion

Personalized loyalty programs have proven to be a game changer in retail fashion, enhancing customer engagement and increasing brand loyalty. They offer tailored experiences, encourage repeat business, and elevate the overall shopping journey. The evolving landscape of retail fashion suggests that adopting intelligent, customer-centric loyalty strategies is not just beneficial but necessary for brands aiming to remain competitive. Looking ahead, these personalized programs are set to redefine customer relationships, making them more interactive and value-driven, thereby shaping a promising future for the retail fashion industry.

To get a first-hand experience about how you too can improve your loyalty programs, book a demo with us.

While the specific number is a playful exaggeration, the reality persists that individuals globally make purchases for various reasons within the omnichannel fashion retail industry.

From fulfilling essential needs to indulging in wish-list items, customers find themselves making unplanned purchases. Most customers have been in those shoes before. We know it takes every bone in your body to convince yourself to stick to your budget, especially if you’re a fashionista.

As a marketer, what if you found a way to leverage this shopping culture and drive repeated purchases through a phygital approach?

The answer to this is Personalized Product Recommendations.

Data from walk-ins can be used for campaigns, and you can present customers with suggestions tailored to their past behaviors and preferences.

Let’s talk about tips to help you use personalized recommendations as a strategy to drive more sales for your retail business.

What you need to know about these personalized recommendations

One major thing to note about these recommendations is that they are hyper-personalized and targeted. Not solely relying on historical user data or general preferences, you can factor in real-time information such as:

• User Behavior:These include the current and recent actions of the customer, including browsing patterns, interactions, and purchase history.
• Timing:Recommendations are adjusted based on the timing of the user’s interaction, considering day, time, or specific events like BFCMs.
• Environment:Refer to data about the customer’s current location, device, and other environmental factors that may influence their preferences or needs.
• User Intent:Understanding the customer’s immediate goals or intentions can help in providing more relevant suggestions.

For example, a contextual recommendation might offer products that are helpful to customers during a holiday season, taking into account the festivities.

But it goes beyond that.

Personalized product recommendations aren’t just suggestions placed in front of customers hoping they’ll buy; they help customers find something they’ll actually be excited to purchase.

It’s a win-win for both customers and brands. Shoppers enjoy a more personalized customer experience, and sellers see boosts in Average Order Values (AOV) and customer retention.

This simple approach here is key in driving repeats.

For example, DODuae.com, one of UAE’s largest online shopping stores, recovered 14.77% of its abandoned carts using WebEngage Journeys.

Here are 5 simple but high-impact tips to replicate the wins in the retail fashion industry.

1. Continue to engage with targeted post-purchase messaging

One mistake that many brands need to correct is ceasing to engage customers with targeted messaging once the purchase is made.

Personalized post-purchase engagement can leave your customers with a positive and lasting impression and keep your brand top of their minds when they need to purchase again.

You can keep customers engaged by helping them get the most out of their new purchases with relevant information or tips.

And this isn’t limited to only online stores, and physical shops can include promotional messages, discounts, or information about upcoming sales on printed receipts.

Taking Nykaa as an example:

If you buy body care products, like lotion, body wash, face wash, etc., from their website constantly, you could get a video tutorial on how to wash your face well or a clip on how to use the products you purchased.

For their physical stores, added tags can be inserted in shopping bags or packaged deliveries with details about loyalty programs or exclusive in-store promotions.

Using our Customer Data Platform (CDP), you can engage with customers through email, in-app messages, push notifications, and more.

Hnak.com, one of the leading retail companies in Saudi Arabia, partners with WebEngage and witnesses a 68% increase in open rates for their cart abandonment emails. That could be your brand, too. Read the full impact story here.

2. Trigger action in real-time

Studying unique customer behavior is important in understanding customers who are making repeat purchases and those who aren’t yet.

When it comes to product restocking, customers typically follow a fixed purchase frequency.
For example, a customer may restock their body care products every 2 months – using that information can help you trigger purchase action in real-time.

You can segment your customers based on their behaviors and send relevant reminders when it is time to restock. Our marketing automation suite also makes it easy to re-engage those who added items to their cart without checking out.

WhatsApp is an ideal platform for this.

As long as they are opt-in to receive WhatsApp messages, you could then send them a push-up notification confirming their order or a reminder to check out while excluding those who have completed checkout in the last 24 hours.

These well-timed reminders are regarded as helpful to your customers and increase their loyalty while driving the repeat purchase rate.

3. Incentivize a second purchase

Everyone loves flash sales, discounts, coupons, and promos. They can be effectively utilized to keep a first-time buyer.

Offering such perks can ultimately drive repeat purchases, but every brand must be careful about doing it too often. It could create a negative perception and impact the brand.

Using analytics, you can see real-time product analysis that will help you make better decisions.

For example, you can give a first-time buyer a 10% discount on their next order. See this as stretching a long hand of partnership with your customers.

You can also incentivize walk-ins, creating a package like a bundle deal where customers receive a discount when purchasing multiple products together.

It’ll be even better if you sell the products together as a bundle offering. You can highlight the amount they saved as an extra push for purchase.

Use retargeting to increase conversions

Every retail store has a long history of cart abandoners. You can switch that in your favor.

Cart abandoners or random potential customers who viewed your site without purchasing can be brought back through retargeting.

The good thing about retargeting is that you can reach customers using ads without logging into an account, even if they were viewing your website as a guest.

Constantly analyzing their behavior and interests gives you insights to create personalized recommendations that will ultimately increase product conversions.

This isn’t only just for online stores.

For example, a physical store owner can find ways to ease the shopping process for busy potential customers. One of them is to introduce a personal shopping service, providing creative assistance to your customers and helping them find products tailored to their preferences.

Then, use this interaction to collect data for future targeted recommendations.

Leverage transactional emails

Transactional emails are automated emails sent to recipients, usually related to account activity or a commercial transaction.

Implement a transactional email campaign triggered by customers’ purchasing habits. The goal is to create an emotional connection that encourages repeat buying.

The thing with email marketing is how versatile it can be used to reach more customers. You can create a user journey using our marketing automation suite, ensuring you’re maximizing sending the right emails to the right customers.

For example, an order confirmation for a face serum is an opportunity to recommend a moisturizer if you find out the user didn’t order one.

Let’s drive those repeated purchases

With a full-stack solution, you will understand your customers, learn how they engage with your brand, and then create personalized recommendations that will keep them coming back.

Choosing the right CDP matters, especially when attempting to convert one-time buyers into repeat customers.

At WebEngage, we spent the last 12 years helping 800+ brands with our easy-to-use campaign management platform powered by our state-of-the-art CDP and marketing automation capabilities that help you create hyper-personalized messages for conversion.

See how we can help you grow by booking a free demo now.

Greetings from WebEngage!

We hope you’re having a great experience with WebEngage. In our monthly releases update, we’re excited to introduce new features on the dashboard.

Advanced Controls for In-app Notifications and App In-line Content

We have added additional controls to our App personalization channels (In-app and App In-line) that will allow users to define campaign view limits, recur campaigns, etc. This includes:

1. Control In-app and App In-line Campaign Views with ‘Lifecycle’

This is an enhancement to our ‘Max limit’ option. It allows you to specify how many times a specific campaign should appear to users and whether it should be repeated/recurred. You can set this through the following two choices in the campaign creation’s ‘When’ tab:

Lifecycle:

• You can set the number of times a notification should be viewed until it’s clicked once, similar to the existing ‘Max limit’ option.
• Recurring notifications can be enabled by ticking the checkbox and then completing the following configurations:
  a. Frequency: Define the frequency limit – Hourly, Daily, Weekly, or Monthly.
  b. No. of recurring cycles: Set the number of times the cycle should repeat; choose a finite value or until the campaign ends.

For a more detailed understanding, refer to our In-app documentation.

Please note:

• For Journey campaigns, view limits can be set, but recurring controls are not applicable.
• Core SDK updates are required for this feature: Android v4.6.0 and iOS v6.5.0. Hybrid SDKs only require updating the core SDK.

2. Frequency Capping Support for In-app Notifications

Users can now fine-tune the frequency of In-app Notifications with two powerful Frequency Capping controls:

1. No. of Views per Session: Define the number of In-app notifications a user encounters in a single session. This advanced control serves crucial use cases, including:

Recurring In-apps: Simplify the recurrence of identical notifications by enabling the ‘repeat the cycle’ option in a single campaign. For example, effortlessly set daily class reminders, ensuring timely notifications for students without manual intervention.

2. Time Gap Between In-apps: Specify the time interval between displaying multiple notifications, preventing consecutive displays for a seamless user experience. This feature addresses various use cases, such as:

Capping the number of notifications within a session: Gain precise control over the number of notifications displayed per session. For instance, manage consecutive notifications during e-commerce shopping sessions, enhancing customer engagement by preventing overwhelming back-to-back notifications.

Please note: This feature would require core SDK updates – for Android, v4.6.0, and for iOS, v6.5.0. 

Watch our insightful video on Advanced Controls for our App Personalization suite for a better understanding of these features.

Premium Feature – API for User Campaign History

We are excited to introduce a premium API that will allow you to seamlessly retrieve all communications sent to a particular user, complete with personalized values. This API empowers you to address important use cases, including:

• Archiving Communications: Keep a comprehensive record of all communications sent to individual end-users.
• Enhancing Customer Support: Facilitate superior customer support by granting teams access to detailed communication histories, including the status of each communication, enabling faster and more effective resolutions.

Please note:

• You can request data up to the last 15 days from the date of execution.
• The API currently supports various communication channels, including Email, SMS, WhatsApp, and Push.

For further information, read our documentation on this premium feature.

New Top Card Metrics for Mobile Push

Embark on a renewed approach to mobile push campaign analysis through this feature. Delve deep into campaign performance with insights on Open-Through Conversions and Revenue, now conveniently available in the Key Metric section for comprehensive analysis. 

Experience a holistic view of your campaigns as you explore the following metrics:

• Click to Impression Ratio (CTOR): Swiftly gauge the impact of your mobile push campaigns by assessing the Click to Impression Ratio. A powerful metric for quick insights into campaign effectiveness.
• Click-through Conversions & Revenue: Metrics that were always available in the Detailed Stats section can now also be enabled for display on the Top Cards.

If you’d like to enable this feature, please reach out to your Customer Success Manager or contact us at product@webengage.com.

Summarized Reports and Metrics Revamp

These enhancements aim to offer you a more intuitive, efficient way to evaluate your campaigns, journeys, and relays.

1. Summarized Reports

In addition to day-wise data, our .csv reports now empower you with Aggregated/Summarized level reports, providing you with a more comprehensive view of campaign performance.

Within the Download and Schedule report modal, a new ‘Data Breakdown’ dropdown provides the following options for stats:

• Day-wise: Retaining the current format, each row represents a campaign/variation’s day-wise stats.
• Week-wise: Stats aligning with the calendar week (Monday to Sunday).
• Month-wise: Stats as per the calendar months (January to December).
• 30 days (Rolling window): Stats up to 30 days, offering a dynamic overview of campaign performance.

For further information, please refer to our documentation.

2. Reporting Columns / Metrics Revamp

Besides Summarized Reports, we have made significant improvements to the reporting columns for a well-structured, seamless experience. Key updates include:

• Streamlined Columns: Eliminated redundant, blank, or non-data columns.
• Enriched Dashboard Metrics: Improved reporting completeness by including missing dashboard metrics like Campaign Start Date, Campaign End Date, Total Impressions, and more.
• New Metrics: We’ve introduced crucial metrics for in-depth analysis, offering a comprehensive understanding of campaign performance. These include Unique Click to Impression Rate, Total Click to Impression Rate, Unique Conversion to Impression Rate, and many more!

Please note: The reports revamp applies to ‘Week-wise,’ ‘Month-wise,’ and ’30 days (Rolling window)’ breakdowns.

To get these enhancements enabled, reach out to your Customer Success Manager or contact us at product@webengage.com.

SDK updates

Android v4.6.0 & iOS v6.5.0

We have added support for the In-app Frequency Capping and Lifecycle features, along with optimizations around the SDK authentication flow.

Hope you explore these features, unlock their potential, and watch your success soar!

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