How to guide: Run personalised experiences using CRM data with the Adobe Analytics & Target – Part 3

In the first article in this series, we looked into how to prepare your implementation for Customer Attributes or CRM data, in the second article we made the configuration and setup in the Experience Cloud as well as uploaded our first batch of CRM data.
In this third article, we will look into a few simple use-cases that every marketing should implement, that will improve user experience and the Customer Lifetime Value (CLV).

If you have followed the first two articles in this serie, you should now have imported some of your CRM data to the Experience Cloud, and have setup your subscriptions for Adobe Analytics and Adobe Target.
You are to start your personalisations adventure, but where to start?

Personalisation comes in different forms and sizes. The most simple form would be as simple as add the customer's first name when they engage with you on your site, in your app or when they opens email marketing from you. However, that won’t be the activity that will ensure high engagement with your site and your brand.

Before we continue, I’d like you to take a moment and think about why you want to run personalisation. What is it, you want to improve? What problem are you trying to solve?

Let’s pretend for a moment, that we are a online retailer. Then our reasons for running personalisation could be to increase average order size or to improve share of returning customers.

We would need to approach both cases different, so let’s start by diving into how we could approach our goal of increasing average order size.

To increase the average order size, I first think of product recommendations. Like we know it from Amazon, Zalando and many other online retailers. We have all seen recommendations like the following, where a retailer tells us that the current product fits with or are often purchased together with other specific products.

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Adobe Target offers marketers to setup this type of product or content recommendations, based on historical data, customer data, Adobe’s AI & Machine learning technology, Adobe Sensei, as well as your own business rules.
If you are not already running product or content recommendation on your site, then I’m certain that just deploying Adobe’s solution using the build-in algorithmes will improve your average basket size.

The recommendation feature of Adobe Target allows you to deploy personalisation at scale, with limited resources and effort.

Another fairly simple personalisation activities, would be to prioritize content at the home page and key landing pages. If you know your customers favorite category or brand, then prioritize content related to those preferences rather than having a static homepage showing what you as a marketer would like to push right now.
You could also adjust the main navigation, based on users interest, making navigation easier on the site.

Often when I hear someone talk about personalisation and what they want to do, they see personalisation only as 1:1 communication with their customers. But there are many levels before you are up and run with 1:1 personalisation with each of your customers and prospects. You need to crawl before you can walk and walk before you can run.
My recommendation to you, would be to start out simpel. Start with some simple activities, that ensure you to quickly being able to launch and evaluate your first activity and then add on from there.

By starting out simple, you may identify gaps in your current tech stack, resources and competences and it then allows you to expand and grow slowly, launching more and more activities and seeing better and better results.

Contact us, if you are considering how to get started with personalisation or need sparring on taking the next steps.