Personalization Doesn’t Have to be Hard
Personalization is no longer a “cool” feature; it’s a user expectation.
More and more users have come to expect personalized content: over 35% of mobile users want personalized experiences and more than 50% of retail app users say that having personally relevant content is the most important element of their experience (eMarketer 2016). Hundreds of articles have been written in the last few years lauding the impact of personalization on conversions, user engagement and retention, and it’s more than hype: a 2016 Demand Metric study found that 80% of marketers reported targeted content as being more effective.
Even with this knowledge, only 30% of marketers have taken major steps to engage their users with personalized content– down from 90% who say they’d like to. So where’s the disconnect? Personalizing content can seem daunting at first. How do you know you’re collecting the right data? Is there room in the budget and do you have the resources to find what you need? Where does machine learning come in? And are you already too far behind?
If you want to implement a personalization strategy but don’t know where to start, you’re not alone. Here are a few things you can do to get moving:
Remember Why You Started
It’s important to remember that your user wants personalization. 86% of studied consumers reported that if a brand provides personally relevant content they are more interested in the brand’s services and products (OneSpot 2017). This is borne out by the fact that conversion rates are boosted by an average of ~20% with use of personalized experiences (Barilliance 2017). These targeted users form a personal connection and are 64% more likely to become evangelists for the brand (OneSpot 2017).
Personalization adds value to the user experience and enriches your relationship with them.
Utilize Known User Properties
The easiest place to start is to see what valuable user data may already be gathering. This information could be on the device side (is the user logged in or a guest?), within your CRM (what purchases has this user made?), or on an analytics platform like Google Analytics or Amplitude (what kind of content are users engaging with?). With this information, you can identify your major user cohorts like new vs. existing users and account holders vs. guests.
Then, it’s time to examine your business goals. What are you hoping to achieve? Do you want to make the experience more relevant for underserved users? Do you want to push users from guests to account holders?
A major US luxury retailer recently used this type of information to begin targeting users based on focus areas for their business. They had a popular app, but knew that men’s shoppers– identified based on their purchase history– were underserved. These users didn’t feel like their app experience was relevant to their needs, and in turn used the app less frequently.
With Prolific’s App Management System (AMS), the retailer was able to create promotions specifically geared toward menswear buyers. They used a feature known as audience tagging within the AMS to prominently position menswear assets within the app any time an identified menswear shopper landed on the home page. The result was an uptick in retention and conversions.
TB12 is another company that’s taken a few simple steps toward personalization. TB12 used to show the same introductory content across the board, but users reported feeling that the content was too generic. TB12 identified users that had been registered for less than a week and established a cohort of “New Users” that is constantly updated. Once this cohort was created, TB12 was able to limit exposure to the “new user” content to actual new users only, making longer-term users feel valued and freeing up homepage real estate.
Use Explicit User Preferences
The simplest way to find out what your users want is to ask them. What are you like? What are you looking for? What would make you come back, or stay longer? It may feel strange to be so straightforward, but people are willing to share. According to Salesforce ~60% of consumers are willing to share personal data in exchange for personalized content (offers, promotions, etc.).
It can be easy to ask for user preferences in an onboarding experience or as part of a guided shopping experience. Here are just two examples of major brands maximizing personalized experiences through specific onboarding concepts:
Scotts built the My Lawn app to assist users in creating personalized lawn care plans. During the app onboarding flow, Scotts asks users to provide their zip code, lawn size, and available equipment– among other things– and inform users that these answers will allow them to provide the most accurate lawn care plan.
These lawn care plans were referenced a few times per season, but Scotts wanted to make the app a daily habit. To do so, Scotts launched a personalized Tips section to provide users with engaging content long after the lawn care plan had been created.
Scotts chose the AMS to quickly create and QA new attention-grabbing content. Because Scotts has captured vital user information during the onboarding flow, they are able to display tips that are most relevant to users and that users are most likely to respond to. This simple step has increased session length and frequency of app launches.
A major US bridal retailer knows that shopping for a wedding dress can be stressful. Brides may know the elements they are looking for, but it can be overwhelming searching through a long catalog of wedding dresses.
In order to combat this issue, the retailer worked with Prolific to build a guided shopping quiz that asks the future bride a series of questions in order to provide a curated set of dress options. Brides can then “favorite” any of the dresses and book an appointment at a brick-and-mortar location to try on the dresses they selected.
The retailer’s team set up the shopping quiz in the AMS, giving them the ability to update questions and answers on the fly, as they learn more about what is important to their potential customers. For example, the retailer learned that desired dress length is one of the factors that brides are most sure about, and least likely to be flexible on. The team then tweaked the importance that the AMS recommendation engine was giving “dress length” when providing results. This change immediately led to an increase in shopper satisfaction.
Since the launch of the shopping quiz, the retailer has been able to directly a attribute high volume of multi-channel sales directly to the guided shopping experience.
Integrate with Recommendation Tools
Another proven method to increase conversions is to provide product or content recommendations based on previously viewed content or previously purchased products. Shoppers who engage with personalized product recommendations are 5.5x more likely to complete a purchase than those who aren’t (Barilliance 2018). Tools like RichRelevance and Certona can highlight recommended products to users, are easy to integrate into your user experience, and provide great results. A large multinational fashion retailer used integrated these tools within their home screen to highlight recently viewed items. By doing so they effectively increased conversions and reduced cart abandonment.
You don’t need to be an expert in personalization to put the products and content your users want right in front of them. By implementing any of these basic strategies, you’ll be on your way to tailoring your content to fit their preferences and habits, bringing you one step closer to reaching your KPIs.