Beyond Basics : Advanced Personalization strategies for Re-marketing Triggers

Re-marketing based on behavioral triggers like abandoned cart, abandoned search and abandoned view are must do’s for any digital marketer to engage customers and bring them back to your site or app. More often than not it’s very tempting to do just the basics, may be your e-commerce platform vendor gives few out of box “widgets” to replay the content or products and you can tick a box and call it done. But that would be waste of a great opportunity to engage with your users fully at the moment they are most interested in your offerings and showcase the full depth and breadth of your catalog.

Imagine your self in the shoes of your customer – They were on your site or app for a reason. Why did they abandon their visit? Are they looking for better price? Are they looking for affordable alternatives? Are they looking for quality recommendations? Are they looking for things that go along with their previous purchases? Are they looking for hot new products they heard about? Or are they just window shopping? May be it’s mix or all of them and you can’t tell. But you can tell a better story than replaying what they have seen. Multi-touch campaigns over their preferred channel with content personalized to each user are a great way to showcase and up sell your offerings.

Here are few advanced personalization strategies to try, going beyond replaying the products your customer has viewed or added to cart.

  1. Related Products : “What Other Items Do Customers Buy After Viewing This Item?” Based on the product that was abandoned you should consider including these in your messages. Very often this is helpful as a first touch in moving your customer down the conversion funnel helping them make informed choices.
  2. Up-sell Products : “What are the top sellers in the category of the item viewed”? Based on the category of the product that was abandoned you can showcase your best sellers from those categories and optionally you can restrict it to specific brands.
  3. Trending Products : May be some of your products are not best sellers yet but they have been recently added to your catalog and are already selling out. Consider including them in your messaging with appropriate call outs.
  4. Affordable Alternatives : Your catalog likely has a breadth of products that are in the same category but are more affordable. Add them as alternative recommendations.
  5. Most Discounted Products : Your customers will likely want “quality” products but want them to be affordable getting most value for their money. And may be you are doing seasonal promotions or roll backs. Consider tying them together to the product and category of the abandoned product.

Depending upon your catalog and the number of touch points you have with your customers you can do all of the above or a mix of them. At Blueshift we have built a DIY Personalization Studio to do all of the above and more without needing to go through development or IT cycles. Re-marketing based on behavior triggers is the most effective messaging you can do as a digital marketer. Do not waste a great opportunity to win over the customer by doing just the basics. Learn more about behavioral triggers with our comprehensive e-book. Learn how our clients like UrbanLadder are using advanced personalization strategies to improve their conversion rates by 400%. If you are ready to take your triggered marketing to the next level say hello.

The Case For Predictive Segmentation – Part 1 of 2

Philip Kotler Segmentation Quote

Retention & Growth marketers are often interested in taking action on a segmented base of users. Classic segmentation methods include

  • Lifecycle based segments: new, active, lapsed etc.
  • Behavioral segments based on user behavior on the website/app
  • Demographic: Age, gender, location, household income, education based
  • Traffic source based
  • First purchase product/category etc.

Given all these ways of segmenting, how should any marketer approach segmented marketing, for the purpose of improving their core retention metrics? Some of the metrics CRM or growth marketers might be interested in improving through a segmented marketing strategy may be around activation rates, repeat purchase rates, or churn/retention rates.

Here are 2 steps for how you can use segmented marketing to drive higher response rate on any metric, say, repeat purchase rate:

  1. Use criteria that lead to a big spread in response rates in the steady state: Researchers on segmentation, have pointed out the need for segments to be  identifiable, substantial, accessible, stable, differentiable and actionable.  In the digital world, the tests on identifiable, accessible, and actionable are often easy to meet with segments. However, what really separates useful segments from the rest is the differentiability of the segment especially in response rates, their stability (i.e. whether the same criteria continue to map to differentiated responses over time), and whether the segments are substantial in size. In other words, you need to identify large segments of users whose response rates are substantially (3-10X) different from the average
  2. Test what happens to the steady state when you introduce a message or an offer: Once you have identified your segments in a steady state, you want to be able to test how you could increase the response rates further by introducing new variables like product features, offers, or content.

We will focus this first post in a 2-part series on the 1st of these challenges:large segments of users whose response rates are substantially (3-10X) different from the average. While this sounds simple enough, in practice, quickly figuring out the criteria that lead to a big spread in response rates could take some work. For example, in a typical setting, your gender based response rates might not look very dissimilar for repeat purchase: Let’s say your average repeat rate is 50%, and that men have a repeat purchase rate of 45% and women 55%. Now, there is clearly a difference in repeat purchase rates, but not enough for you to build compelling campaigns around it. At the other end of the spectrum, you might be able to identify outlier users, whose response rates are very high – but these outlier users may not meet either the stability test (e.g. will they continue buying the same way), or may not be a substantial enough segment.

This is where predictive segmentation & machine learning have a role to play. Machine learning can quickly figure out variables that are important, and combine them to come up with models that give you a 3-10X separation on large buckets of users. At Blueshift, we make this easy by making predictive segmentation scores available “on tap” for you to use.

Blueshift Predictive Repeat Purchase Score

Visualization of predictive score percentile with corresponding repeat purchase rates

For instance, in this graph, you can see how multiple variables have been combined to generate a repeat purchase score that gives you a nice spread in predicted response rates. In this example, users in the top 10 percentile of scores have a 90% repeat rate, whereas users in the bottom 10 percentile of scores have a repeat purchase rate of only 9%.

Now that you have identified a way to find segments of users who have a much higher response rates than the average in the steady state, how do you test the actions that will help you improve these metrics? Our second post in this series will look at that.

Using Behavioral Messaging to Drive Higher Response Rates [Infographic]

Marketers have known that timely and relevant messages, tailored to a user’s behavior, are more impactful than batch and blast emails. But just how effective can these behavioral messages be? And how can you incorporate them into your marketing plan?




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<a href=""><img alt="Using Behavioral Messaging To Drive Higher Response Rates" src="" width="100%" /></a><br><p><small> Brought to you by <a href="" > Blueshift: Predictive Marketing Automation </a></small>

Relationship marketing to the perpetually connected customer

With multiple devices at their disposal, a customer’s path to a digital purchase now often spans both a mobile device and a desktop.  As an NYT article pointed out, “85 percent of online shoppers start searching on one device — most often a mobile phone — and make a purchase on another.” Comscore has declared that 2013 was the first year when the majority of users became “multiple platform”, i.e. they were accessing the same digital properties across multiple desktop and mobile devices. Indeed, Forrester has coined the term “perpetually connected customer” (PCC) for someone who owns and uses at least 3 connected devices, and thinks that close to half of online adults are now PCC.

These multi-platform perpetually connected customers are also becoming addressable in new and interesting ways at large scale:

  • As of last year, Apple had already sent 7.4 trillion push notifications through its iCloud service on iOS and Mac
  • Due to high social media consumption on mobile devices, Facebook’s FBX was already serving billions of retargeting ad impressions as of mid last year

Gone are the days when digital relationship marketing could be equated with just email, and the expectation that the email would be opened on the desktop. Today’s customer is engaged through variety of messaging techniques on multiple devices, and relationship marketers have to catch up to that reality.


Today's hyper connected shopper

Today’s hyper connected shopper

But therein lies the challenge: how is the marketer to unify all the information about a customer, and engage with the customer with the right message and deliver it on the right platform, using the right channel? Take something as basic as an abandoned cart reminder, which in the old days was simply a triggered email. How do you scale a simple campaign like that to target the perpetually connected customer on the right channel, intelligently switching between email, push notifications and retargeting?

We have 3 tips for marketers to adapt to this brave new world:

  1. Stop treating platforms and channels as silos: In this multi-platform world, the article goes on to point out, platforms and channels cannot be a silo anymore. As the NYT article points out, Jason Spero, director of mobile sales and strategy at Google, slowly came to the realization that you can’t ‘put mobile in a silo. It’s also about the desktop’. Similarly, you can’t simply treat channels like email, retargeting and push notifications as silos in themselves; the optimal strategy would be to find the right channel and the right platform for each user.
  1. Move away from list pulls to personalized triggered communication: Relationship marketers have long been to a model of defining target audiences, and “pulling lists” that match these criteria, and setting up campaigns that get delivered in batch mode to the entire list. However, in the perpetually connected world, the customer values personalized communication in context. Moving towards personalized real time triggered messages, instead of audience based batched communication, is the best way to engage the customer throughout their lifecycle.
  1. Develop unified attribution and testing to measure true lift:  In the multi-platform, multi-channel world, testing new strategies requires superior discipline on measurement and attribution. As a simple example, if you spend dollars on display retargeting on a mobile device, how can you truly understand whether the customer would have purchased anyway, through other free messaging channels like email or push notifications? Despite knowing that techniques last click attribution have deep flaws, marketers have often lacked tools that help them measure the true lift.  A/b testing methods that only show channel level metrics in a silo need to be replaced with techniques that measure the impact of various levers on treated and holdout populations across channels and devices.

At Blueshift, we are building solutions to address these challenges (sign up to stay updated on our launch). But in the meanwhile, we would love to hear how you have been solving them.