Personalization is the invariable tool of choice for businesses that are actively trying to “delight” their customers. By offering personalized, memorable user experiences across all channels, businesses are aiming to convert their prospects and customers into lifelong customers and evangelists.
Building a personalized experience for users starts with learning their behavior individually. Your customers are providing you information about their preferences and intent across all digital touchpoints. Whether they are browsing specific products on your eCommerce website, reading particular articles on your news app, or booking certain holiday destinations on your travel portal, they are offering you valuable insights on their preferences and intent. Even minor activities such as engaging with emails, sharing your content on social media and adding products to a wishlist can help you understand your users’ personas better.
However, with the growing suite of digital channels, the number of touchpoints with your users is increasing at a massive rate. For instance, you can reach out to users over website, mobile app, email, digital ads, push notifications, SMS, and more! Tracking and documenting activities and behaviors of users across all these channels can be an arduous task.
To tackle this situation, modern marketers strive to host all information about a user — demographic and behavioral — at a single place. This allows marketers to have a unified view of each user and a single source of truth.
Unified view of customers — How it works
Let’s discuss this with an example of a hypothetical eCommerce user, Amy. The below image represents the unified view of Amy’s persona:
The unified view above offers a deep understanding of Amy’s behavior on a particular eCommerce store. The unified view covers not just her profile and demographic data, but also data on her affinities and preferences, and intent. All these data points have been collected from multiple channels (website, mobile app, emails, push notifications, etc.), which Amy used to engage with the eCommerce store.
With the help of this unified view, we can deliver customized marketing campaigns for Amy. For instance, the eCommerce website and mobile app can display a personalized product feed for Amy based on her interests. Further, emails and notifications can contain offers on Amy’s favorite brands. The timing of the marketing campaigns, too, can be determined using the unified view.
Let’s discuss how marketers can take advantage of a unified view of customers and build their campaigns accordingly.
Offering 1:1 Personalization to Customers
A unified view of each user allows us to learn which products, articles, software, or travel deals a user would be the most interested in. Coupled with an AI or machine-learning engine, you can track a user’s behavior evolving over time — and let their unified view evolve as well.
The AI-powered recommendations can then be inserted into communications across multiple channels such as emails, website/app widgets, lightbox popups, push notifications, SMS, and more.
These AI powered recommendations are expected to garner a higher engagement rate with your audience. For example, Snopes.com doubled their website visits and email open rate using AI-powered recommendations.
Here is Snopes.com’s AI-powered recommendation widget in action:
Segmenting Audiences in a Smart Manner
A unified view provides you details about even the most minute activities of your individual users. It gives marketers the power to create powerful segments of users based on their activities (or a combination of activities, known as behavior). These segments can then be targeted appropriately with hyper-relevant messaging.
For example, a Media business can create a segment of users who haven’t browsed its website/app in the past 2 weeks, and send them re-engagement campaigns over email or push notifications. Similarly, a Travel business can target users who haven’t made a booking in the past 4 months and send them lucrative travel deals. The possibilities are endless; you can make segments as elaborate as you want.
Let’s consider a real-life case study. Nykaa, a beauty eCommerce brand, ran highly-targeted email campaigns by creating deep segments of its prospects and customers. A few of their segments were:
- Highly engaged users: Users who engaged with Nykaa’s emails (by opening or clicking its emails) in last 30 days.
- Bought a certain brand: Users who bought a specific brand, e.g., users who bought L’Oréal products.
- Order value: Users who’ve purchased items worth over a certain amount, e.g., users who purchased items worth over $50.
- Category specific segments: Users who purchased items from a specific product category, such as women haircare products.
Below is an email campaign that Nykaa sent specifically to users who were interested in the brand L’Oréal.
Connecting with Users at PrimeTime
Marketers will now be able to learn what time in the day and week is the most engaging for each user. The unified view of a user will document all the times when a user opened an email, clicked a notification, browsed the app for long, and more. An AI-engine can hence learn the perfect time to engage with each user and provide that information to marketers.
Essentially, you can schedule your marketing campaign at a different time for each customer! This feature in ZetaHub is known as Prime Time Messaging.
ZetaHub’s Prime Time Messaging optimizes campaign delivery on an individual basis to drive deeper content engagement, product sales, or other conversion goals.
It’s important for marketers to understand your users’ likes and preferences and offer them your services accordingly — now more than ever. You can achieve that by having a unified view of each user’s activities and behavior. Unified view of users, together with an AI-engine, will help you create highly effective marketing campaigns.
Is there anything you would like to add/change in the article? Please share in the comments section below.