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Thanks for reaching out! While you wait for confirmation from an Apptentive team member, you may find these free resources to be of interest:

Guide

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Guide

The Five Stages of Reducing Mobile Customer Churn

Retention is a top priority for mobile marketers. Our new five-step framework is here to help you improve your existing strategy.

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Guide

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Guide

2020 Mobile App Engagement Benchmark Report

Apptentive’s annual mobile app engagement benchmark report serves as a baseline to help app publishers across categories understand their app’s engagement strengths and areas for improvement.

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How to Increase Purchases with Mobile Retargeting

Pratheet Vinjamur  //  January 3, 2019  //  3 min read

Today’s retailers are working on product diversification strategies—and the latest question on every e-commerce player’s mind is, “How do I increase the lifetime value of my customers?”

As companies became more advanced in the digital space, so did advertising solutions—particularly on mobile. One of the first things that might come to mind here is retargeting, and rightfully so. Retargeting allows mobile commerce players to place targeted ads based on the past purchases of their customers.

Retargeting, if done badly, can sometimes come across as irritating (we’ve all been chased across the internet by ads for things we just purchased). However, if used in the correct way, it can pay huge dividends. So why are retailers failing to deliver messages that resonate with people’s needs? Why aren’t they surprising consumers, and ultimately making them spend more?

It’s time to assess the retargeting options that mobile has in store for e-commerce.

Data sources for mobile retargeting

Unlike retargeting on desktop, where people are targeted based on cookies, retargeting on mobile uses other sources of information to track people across in-app environments, create profiles, and show them relevant ads. The data sources needed here are:

  • Mobile device IDs from the devices that choose to share them
  • First-party data about any user interaction within the app, product ID, offer details, and deep-links provided by the advertisers
  • In-app inventory from ad networks

Smart retargeting strategies for e-commerce

Once all data sources are available, it’s important to evaluate which data points must be considered in order to retarget the right people with the right products. Typically, app retailers achieve the best results when looking at the purchase history of their users, along with their individual attributes. Here is how that’s done:

Keep segments up to date

To avoid targeting people with products they have already bought, user segments must be up to date. Dynamic customer segmentation tools take care of that in real-time. As soon as a purchase is made, the user in question is removed from a particular segment, meaning they don’t see the same products again.

Sometimes the same thing is perfect

With all the talk around product diversification, it’s worth noting that promoting the same product makes sense under certain conditions.

If a user has added an item to their cart but has not followed through with the purchase, retargeting provides a chance to remind the shopper about that particular product. This tends to work well within 24 hours of the item being dropped into the cart.

With fast moving consumer goods (FMCG) or services that are renewed on a regular basis, retargeting can also be powerful in encouraging specific consumers to spend more on the products they have already bought. Offering enticing discounts is a proven winner here.

The many facets of product diversification

Since there is a limit to the number of products a person can buy repeatedly, retailers can maximize their revenue by expanding their product range. The following graph highlights how retailers can reach the highest revenue per user by recommending diverse products via retargeting.

When starting to retarget a user, retailers can show more ads of the same product, which can increase more revenue per user. This uplift will only last until a certain threshold (level x). To increase the revenue per user beyond that, retailers can cross- or up-sell to achieve the maximum revenue per user.

When diversifying a product range, retailers must also take into account certain conditions. Utilizing a cross-product recommendation engine is key to offering people additional products that complement a purchase and providing a better shopping experience. Smart engines learn about consumers and make personalized suggestions for products they might like to buy. Let’s take a quick look at some examples:

Cross-selling based on products: T-shirt → Jeans
Up-selling: Jeans → more expensive Jeans
Cross-selling based on attributes: TV, Sound System → Video games

Sell people the right products

Diversifying a product is one thing. Selling people the right one is another. With sensitive and smart mobile retargeting tools and strategies, companies leveraging mobile commerce will achieve this and ultimately maximize their revenue per user.

About Pratheet Vinjamur

Pratheet is the Head of Retargeting at Glispa, a mobile ad tech company. He is an experienced industry expert, having worked in both ad tech and as an adviser to startups for online marketing. Connect with him on LinkedIn.
View all posts by Pratheet Vinjamur >

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