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by: Zank, CEO of Bennett Data Science

Customer attention

It’s no mystery that there’s a lot of competition for your customers’ attention. Reports say we see up to 10,000 ads per day. Per DAY! That’s astounding.

It starts when many are still in bed, checking social feeds, maybe the news, some weather and eyeing the morning commute.

And each of those outlets can (and in most cases does) show ads. But the ads aren’t the only source of content designed to get your attention. It’s widely known now that the sources we turn to such as Facebook, Instagram and news sources all design their content and messaging in such a way that it’s personalized just for you. Or, rather, just for you to engage with.

The one that gets me is in LinkedIn, just after I accept a connection request. There’s a page that shows new faces of people I’m not yet connected with. It’s so engaging that I can’t help but scroll through a few screens. It’s so magnetic to me that I’ll sometimes hold my hand up to block the screen if I know I don’t have the time to surf through a few hundred new faces. And to LinkedIn’s credit, that’s no mistake!

What are these companies doing to garner such rampant adoption? Why are they so engaging?

From a high level, it comes down to a couple of very well executed initiatives:

  1. A fantastic user experience. Generally, this is not personalized for each user. In other words, the grid I see in my LinkedIn recommendations is the same grid (but with different faces) that you see. The spacing between images, the colors, the amount of data presented, the shape of the images. It’s all part of a stellar user experience. But this isn’t the personalized part.
  2. 1:1 personalization.1:1 personalization means that every user gets an experience unique to the preferences of that user, insomuch as data scientists can ascertain what that might be, given the available signals. To stay with the LinkedIn “Recommended for you” example, this means that you and I wouldn’t see the same images, because we each get personalized results based on all the signals LinkedIn has collected about us and all its other users.

It’s worth mentioning that good user experience has to be tied to personalization and vise versa. One without the other would be much less effective. Together they’re synergistic.

You’re probably aware that consumers expect (maybe even demand) personalization these days. But you’re (probably) not LinkedIn.

So how does any of this apply to you?

Well, let’s imagine you have a Shopify store and you’re selling 50 products to thousands or hundreds of thousands of users. You’ve got a great, scalable platform and things are going well, but you want to be able to do a few things to increase revenue, such as:

  1. Reach out to old customers with a new offer, personalized to what they purchased from you previously
  2. Show add-on items to a cart based on what’s generally kept with the same or similar cart contents
  3. Predict when a customer is likely to churn so you can reach out and keep her from leaving

These are just a few of the initiatives you can crush with 1:1 personalization. It’s the difference between sending out one, generic email with your most popular products, and seeing out a special, unique message to each one of your customers.

And the benefits?

They speak from themselves.
From Forbes, personalization:

  • drives impulse purchases – 49% of customers make impulse buys when presented with a personalized recommendation
  • leads to increased revenue – 40% of customers surveyed say they spend more due to a personalized recommendation
  • results into fewer returns – When personalized recommendations were purchased, only 5% were returned and 85% of impulse buyers were happy with their purchases
  • leads to greater customer loyalty – 44% say they’re likely to repeat purchase after a personalized experience

If you’re interested in learning more about building 1:1 personalization into your products or efforts, please let us know. We’ve helped big and small companies achieve great results.

Zank Bennett is CEO of Bennett Data Science, a group that works with companies from early-stage startups to the Fortune 500. BDS specializes in working with large volumes of data to solve complex business problems, finding novel ways for companies to grow their products and revenue using data, and maximizing the effectiveness of existing data science personnel.

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