Enabling Dynamic Personalization Through an AI-powered Single Customer View

For marketers today, the holy grail is no longer just customer acquisition; rather, they are increasingly focusing on growing the lifetime value of the customer by improving customer engagement and retention. Artificial Intelligence (AI)-powered solutions can help achieve this through hyper-personalization and a seamless user experience across devices.

In an earlier blog, we discussed how personalized marketing could drive better conversion.  For online businesses, personalization forms the backbone of user experience and revenue growth. However, in a survey conducted by eMarketer, 91 percent of decision makers acknowledged that their companies needed to improve their personalization capabilities.

Many enterprises are unable to truly personalize their marketing campaigns simply because they lack the single customer view (SCV) that is essential for personalization success.

The Limitations of Marketing Automation Tools in Developing an SCV

Put very simply, SCV consolidates customer data from your different marketing and customer service channels in one place; thus, offering a complete and comprehensive view of your customer. This, in turn, can help you create better targeted and personalized messages that boost interest, engagement and conversion.

But implementing this is easier said than done. Across the region, companies face a number of challenges when it comes to effective personalization through SCV:

1. As the number of touchpoints grow, with customers browsing, evaluating and purchasing products across devices, companies must communicate with them across devices and channels as well. Often companies lack the technology needed to map the same customer across different devices, and this leads to an inconsistent customer experience.

For instance, a marketer may reach out to the same person with the same message three times on three separate devices, simply because their marketing automation tool did not recognise the customer as one person. In a different scenario, if you send a push notification through a marketing automation tool to remind a shopper of something that she has already purchased, this information would be irrelevant or even annoying.

2. Current marketing automation and data gathering tools (email marketing, google analytics, social listening, etc.) allow companies to access vast amounts of customer data, but with these acting in silos, the data is dispersed across different databases. The result – a fragmented customer view.  

3. Marketing teams are able to gather data about their customers’ behavior and journeys on the website and company app, but lack details about what the same customer do outside the company’s online platforms, leading to an incomplete picture of the customer.

Using AI to Build an SCV for Personalization Success

This is where artificial intelligence solutions can help. An AI-powered proactive marketing automation solution like Appier’s Aiqua, for instance, automatically links your audience across devices. To achieve this, the system requires a massive amount of user behavior data, which comes with Aiqua and a brand might not have in a short time. AI will then find the patterns through the data and link back to a specific type of users and the devices they own. This gives you a consolidated view of each customer’s activity and lets you engage seamlessly with them across devices.

Additionally, it maps their journey inside your platforms with their behavior and interests outside, offering you a comprehensive view of your customer’s complete online behavior.

With this data, you can hyper-personalize your marketing campaigns and engage with users across devices by sending out your messaging at the right moment on the channel or device that is right for each user.

With AI enabling marketers to understand and identify audiences based on interests outside of the company app and website, such solutions become integral to customer discovery as well – allowing you to decipher user preferences before they even engage with your site or app. Using the data consolidated from various channels, marketers can then personalize content for customers who have not even engaged with them as yet, making messaging relevant and specific.

For example, a marketer at a travel company can identify which users are likely to be interested in traveling to France even before they land on the website. They can reach out to these prospects with personalized messaging meant to arouse interest and also proactively set rules to personalize the content of the website on the prospect’s first visit.

AI-powered SCV hence allows you to hyper-personalize marketing and offer customers products that they are actually interested in, thus shortening the purchase cycle and driving conversion. Use SCV as a foundational platform for your cross-channel marketing efforts and leverage the insights derived from the data to target the right customer at the right time on the right channel.

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