While technology has been available for years, strategy has lagged behind. Let’s investigate why. (ecommerce platforms)
You’ve probably heard that personalisation is a “must-have” strategy for every serious internet business unless you’ve been living under a rock for the past three years. And the desire to adopt it is undeniable: According to a report conducted by Clearhead in December 2016, over 60% of online shops have the technology to personalise their products.
So, everything’s fine, right? Almost everyone is on board with personalisation, so we can move on to the next big thing and acquire some new, flashy tools.
Not so fast, my friend.
According to the same Clearhead report, while most online shops have personalisation technology, few know how to use it effectively. Only 17 percent of the 144 ecommerce executives polled for the report had a plan in place to provide personalised experiences.
“As with testing, we’ve discovered that a lack of technology isn’t a barrier to personalisation. While 64% of retailers have the technology, Clearhead Co-Founder and Executive Chairman Sam Decker argues in the recently released Digital Optimization Benchmarking Study that they “tend to lack the methodology and rigour needed to execute their customization efforts.”
What makes personalization such a difficult technique to implement? Assume you have the necessary technology, a large amount of usable audience data, and plenty of time. Following that, there are three major roadblocks that marketers must overcome before customization becomes mainstream:
1. How do you segment your audience before personalization? (ecommerce platforms)
One of the first concerns a marketer must address is how to segment the audience into groups that are worthy of personalization. It’s pointless to waste time developing personalisation tactics for audience segments that don’t exist or aren’t actual customers.
Even deciding which data points to use might be a difficult task: What matters more, the fact that it’s night there or the fact that it’s raining outside? Is it more vital to be male or female, or is it more important to be older? The list goes on and on, and there isn’t enough time or traffic on the site to try out all of the possibilities.
More.. (ecommerce platforms)
Not to mention the fact that these segments are continually altering with the seasons, making this chore even more challenging.
The quick fix is to go backwards in time. Start with the data point for which you have a good personalization notion and which is relevant. Should the content you show them be generic? For example, if your visitor is a repeat visitor or came to your site via a specific keyword search, should the content you display them be generic? At the very least, you’ll be halfway there if you can “personalise” depending on a data point.
Long-term solution: Continue to experiment with different data points to utilise as personalization criteria.
2. What does it mean to have a tailored experience? (ecommerce platforms)
Optimizely made personalisation look so easy when it first debuted it in mid-2015. CEO Dan Siroker demonstrated how a Skymosity integration might be used to find out what the weather was like where your visitor was located and then modify a homepage banner based on that information. So, if it was sunny for your site’s visitor, you could display a surfer wearing this season’s board shorts, and if it was raining, you could show someone in the rain wearing a poncho. Personalization is now complete! People who live in hot climates desire board shorts, and if it’s raining, they’ll want a poncho. Aren’t we all just a bunch of apes? It’s not that straightforward in practise (and Optimizely is well aware).
Apart from presenting return visitors product categories they’ve already looked at rather than whatever is on offer that day, the plan for what to do in reaction to any data point is hazy after you get beyond the basics.
So what if you know I’m a podcast listener, work in Manhattan, and recently married? Will any of that assist you in determining the best way to sell me something? Is it true that just because I’m a man, I enjoy seeing other men dressed up? Maybe I’m out shopping for my wife. What evidence do you have? Will you rely on me returning to the site after expressing an interest in something, thus only personalising for a small percentage of visitors?
Even if you find a generic strategy for a given data point, are you confident that your adjustments are working as intended? Is there another consideration that you’re overlooking?
With so many inquiries, it’s easy to see why the ordinary marketer wouldn’t want to deal with personalisation when there are more straightforward options available.
The quick fix is to keep things simple. Men and women shop in different ways. It’s possible that past behaviour predicts future interests.
The long-term solution is to continue testing in order to discover more productive experiences. Rather of aiming to create the most individualised experience possible, concentrate on where you can get the most bang for your dollars.