Mandy Steinhardt
Mandy Steinhardt
January 12, 2018

Data Mining for Personalization: Questions About Customers

In one of our recent blog posts, we walked through the questions businesses need to be asking themselves to make personalization work. We explored matters like minimal viable data and responsible data storage, as well as how businesses can look to their own industries for guidance.However, we don’t want to forget a group so crucial they deserve their own post – customers.

Making Personalization Work From the Customer Perspective

As we discussed in our previous blog post, calls for personalization are on the rise. Today’s shoppers recognize the benefits of customized digital experiences, and every positive personalized interaction leaves consumers wanting more.

But delivering great personalized experiences is easier said than done for businesses. Personalization can mean different things to different people, so brands must figure out how to create experiences that resonate and delight at the individual level. At the same time, with new capabilities developed every day, brands toe a fine line between doing too little and doing too much.

To balance these factors, businesses must make it top priority to more deeply understand their customers. This customer empathy helps stakeholders grasp what audiences are looking for, as well as which personalization tactics they may not be ready for just yet. Learning more about user experiences provides the bedrock of smart business decisions. And this isn’t just a one-time job, but a life-long commitment. Customers’ expectations are always changing and new factors regularly emerge to influence their desires. Improving experiences over time requires constant questioning.

Here are two personalization-related questions we’d like to see all businesses asking about their customers more often when evaluating their uses of data:

What’s motivating consumers to share information?

Technology’s role in practically all areas of life has helped more people feel comfortable sharing things about them with these systems. However, people won’t always provide their personal information willingly. There’s a major difference between what you can do with data that users have willingly volunteered versus data that you have purchased or hoarded over time.

Context matters. For example, when joining a retailer’s loyalty program, shoppers will give up personal information in exchange for appropriately personalized experiences, such as shopping recommendations. That’s the expectation in retail.

However, expectations are likely different when it comes to the depth of information collected and shared through our social network logins. While users share their email address or phone number with social networks to create profiles, as well as their interests and even events that they plan to attend, people forget how connected their digital identities are. Facebook may be sharing this data with a number of other businesses that have requested certain permissions via Social Login, and that’s OK. But Facebook’s users will likely be turned off if these brands start using and displaying this data in personalized communications.

The same goes for emerging voice-controlled devices like Siri and Alexa. People understand on a basic level that having these technologies demands sharing personal information, but Apple and Google must still be cautious about how they leverage those details.

We’re OK with these companies using our data if it’s completely in service to us, and as long as we’re not constantly reminded about companies virtually peeking over our shoulders or listening to our Siri requests. For instance, many people are still wary of intelligent systems drawing on new and prior pieces of information to proactively personalize experiences. If Siri said “Hey Mandy, your mom’s birthday is tomorrow. We know she likes flowers. Would you like to order some?” this messaging would reach beyond many consumers’ comfort levels.

What is my customer’s ideal journey?

An easy way to avoid over personalizing is to always come back to your customer’s ideal journey (more on that here). This helps determine if you’re collecting customer data to truly benefit users, or just because you can.

You should have an identified reason for every piece of information you access, and relate this data back to a clear customer benefit. Collecting more data just because that’s what other companies are doing is dangerous and careless. Rather, with a clearly defined customer journey and intended business outcomes, your team can determine what type and depth of data is necessary to personalize experiences along the way.

This is really a two-part question. With your customer’s ideal journey in mind, you then have to ask if you’re balancing your own ROI with real benefits for users. Marrying these two objectives results in personalized experiences that work for both parties.

For example, if you’re considering having chatbot technologies handle customer service needs, ask if you’re adding the solution to make customers’ experiences better, or because it saves money. The latter isn’t a bad motivation, but alone it’s not enough. Shoppers will be mad if you’re diverting them down an endless path with little payoff, but not if you’re passing them to a chatbot that provides real value and effortless resolution.

These two questions are certainly not exhaustive, but they’re a start to help businesses approach personalization with a customer-centric mindset. Get in touch with our team to talk through these questions and learn which ones you should be asking next.

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