Personalization Pioneers: 4 Ways to Increase Personalization

We are only a few years off from personalization being everywhere and anywhere, merging our offline experiences with the digital world. It’s not just consumers that need to be prepared, but the brands that need to deliver on that promise and create better content faster.

Preparation for a personalized world doesn’t only mean deploying recommendation widgets to sell more product (though they are nice, too), but instead, using data to actually create the products and experiences audiences actively like and want to consume.

Take Netflix, for example: the company takes personalization to the next level. There are millions of versions of the website active at any given moment and the brand uses the data to actually commission shows based on what people like, not just recommend them. The results are pretty resounding. On average, the success rate for a TV show is 35%. For a Netflix original series like “House of Cards,” that number hovers between 70-80%.

And sometimes, maybe it is about product recommendations. If brands are going to play in the product recommendation space, they should do it well and in a way that will achieve maximum benefit to the customer and positively affect the brand’s bottom line.

Personalization is about more than simply recommending a product and hoping your customer buys it. The functionality can be used to extend the customer journey beyond the point of transaction to cover the entirety of the customer experience and provide solutions to user activity, not a pain point against them.

For example, there’s no need to send someone that 20% off coupon a day after they spent $1,000 at your store online—it will likely just annoy them if you do. We’re not saying don’t run the promotion, just be specific about who you send it to.

But why stop with digital? Take it even one step further and use personalization to connect the real and online worlds through kiosks, call centers, POS systems and CRM, to name a few.

We live in a nuanced world that we can uncover with testing and insights with every step or keystroke. However, we rarely use those tools to their fullest potential. Brands are continually becoming more comfortable with A/B testing to drive future strategy and optimization efforts.

Testing is perhaps the most important component of a strong personalization practice. The more information generated, the more opportunity there is to align more closely and resonate with an audience.

But what if we could test and optimize in real time? Personalization is not only for recommendations, conversions and products, but it also allows brands to test templates for engagement. AI learning in the moment allows brands to be nimble and favor the winning solution immediately and automatically.

For the customer, it positively affects their experiences by giving them the information and products they are specifically looking for in a way that mimics more closely the blended discovery one has in a real-life experience such as walking into a store for one thing and coming across another. And for the brand? The result is an immediate shift toward a more engaging module that encourages audience interaction and ultimately, additional sell and conversion.

Personalization is important because it ultimately affects the bottom line. It’s about conversions and making those conversions as easy as possible for the customer by showing them something they are actually interested in.

With data, brands have the ability to identify user affinity and more effectively predict recommendations and other functionality. Affinity can be vast and specific. It is also not limited to company websites. Brands should use it to close the loop with campaigns on alternative platforms like Facebook and Google with lookalike audiences and circle the experience for those groups back online.

That’s especially helpful since affinity-based models work very well when brands don’t have a lot of information about the specific user, and personalization AI can determine affinity in only a few clicks through an experience.

When you have no data about the user at all—use what you do have. For example, outdoor gear company Fjallraven uses data about the weather. The brand created multiple MP4 banners for every type of weather situation and showed appropriate ones to customers in real time. If it was raining in their location, they saw rain jackets and waterproof gear first. Snowing? Winter parkas.