How to Leverage Different Types of Data to Personalize Your Customer Experience

As a modern marketer, you probably have a ton of customer data at your disposal. And much of that data likely comes from the mobile channel thanks to the power of apps to collect first-party insights on users. But if you’re like many of the marketers that work with us, a lot of that data might as well be in your disposal. Don’t let your mobile efforts go to waste. Leverage your data to create a favorable impression of your brand, and foster good-will and long lasting loyalty. Need some ideas about how to do it? Check out our tips for how to leverage different types of data to personalize your in-app experience!

Behavioral data

Leveraging your customers’ purchase and browsing history is perhaps the most powerful way to personalize their in-app experience. Each customer has unique tastes and needs that require equally unique and individualized engagements. There are a few different ways to do this.

One way is to suggest items to consumers based on things they have previously purchased or browsed. This is a tactic that e-commerce giant Amazon is well-known for pioneering. By tapping into a customer’s purchase or browsing history, brands can then algorithmically determine other items they would be likely to purchase, and use this information to send the customer an engagement promoting that “next best offer.”

Brands can also build mechanisms to gather information from consumers about their favorite brands and items. For example, once a customer has created an account, brands can give users the ability to save “favorite” items as they browse and set up personalized alerts when those items are low in stock or go on sale. Retailers can also enable customers to select favorite brands to receive notifications when more inventory becomes available.

Location data

Using intelligent data collection, mobile bridges the gap between offline and online behaviors, enabling an awesome cohesive experience for customers. Brands can identify locational data (as well as other key attributes) to append to customer profiles the moment they happen and set rules for any of those attributes to trigger a personalized experience. For example, when a customer trips a geofence upon entering a brick-and-mortar store, send them a push notification to say welcome and that items they were browsing online are available in-store.

Nordstrom has started to leverage customers’ location data to take exceptional experiences from in-app to in-store. According to Luxury Daily, Nordstrom is testing a program that will notify store employees when a customer who has reserved an item through the retailer’s app arrives in-store, which will then enable employees to arrange a dressing room with the customer’s items and name on the door.

Even if your current tech stack doesn’t include geofencing capabilities, your brand can still leverage location data to improve the customer experience. By simply giving your customers the ability to identify their geographic preference or current location, you’ll gain valuable insight that can be used to trigger personalized engagements, like this one I received from Chairish:

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Survey data

Brands tend to focus on providing discounts and gifts to happy customers, which is an important piece of the customer loyalty puzzle. However, we’ve seen that many brands overlook the value of incentivizing less frequent or less happy customers as a way of increasing their loyalty and satisfaction.

One way to distinguish between these two groups and act in real time at the moment of impact in a personalized way is through surveys. Immediately following a customer’s purchase, send him a brief in-app survey asking the individual to rate his experience among three options–great, just ok, and disappointing. The subsequent engagement will vary depending on the customer’s response. For example, the customer that responds just ok or disappointing will receive an offer for a discount on the next purchase; whereas, the customer that says great will receive a customized link to refer a friend to create an account.

Time is of the essence when it comes to surveys. They’re most effective when delivered when a purchase or transaction has just been completed. For example, Instacart sent me a push notification prompting me to rate my experience mere moments after my order had been dropped at my door.


Usage data

Besides the treasure trove of data that mobile unlocks, it also provides many ways for brands to engage with consumers. There’s push, in-app messages, and mobile inbox–all hitting consumers on a device that’s more like an inanimate best friend.

There are lots of best practices when it comes to using these messaging techniques. One that is often overlooked is time of delivery. Many brands seem to choose two times of day to send their push messages–once mid-morning and once mid-evening. While this timing is likely based on some industry benchmarks, there’s an opportunity to increase message engagement and conversion rates by adjusting the time of delivery based on each individual consumer’s historical app usage data. This is an easy adjustment that has the potential to deliver big results.

For example, I received a push notification from Joss & Main to remind me about Black Friday and Cyber Monday deals. As you can see below, the message came in at 1:28 AM, several hours later than the usual bedtime scrolling and shopping I do on my phone before lights out.

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If I had received that first push just a bit earlier I would have been much more likely to have browsed.

Your data isn’t a nice-to-have; it’s a need-to-have, and a need-to-use. Mobilize your data to personalize your customer experience experience from in-app to in-store and all the channels in between. That’s the simple secret to building a brand that customers love; love that translates into lasting loyalty.