Effective personalization undoubtedly improves a brand’s sales. If a brand understands who I am by showing me content and products relevant to me, I’m much more likely to transact with them than if I were shown generic content and products.
For years websites have dabbled with personalization by simply displaying recommended products to users under the guise of ‘you may also like’ or ‘other customer’s bought,’ but how effective are they really? How much do these really increase a website’s conversion rate?
We’ve all seen poor examples of this, and even Amazon isn’t perfect: after buying a Nintendo Wii game, they recommended that I buy the Wii console. You can see why that might happen, but it was certainly not a great recommendation.
Personalization can take many forms, from recommended products, personalized content, banners, product lists, emails, or offers and promotions. If implemented cleverly, users should not even realize they are being targeted with personalization. Used correctly, personalization can be a very powerful tool for commerce and can help drive sales across all channels.
However, if implemented poorly, personalization can have the opposite effect. If the personalized content or products miss their target, it can actually reduce conversion rate.
What makes personalization effective?
So how do we get personalization right? How do we make sure that the content is actually what I, the customer, wants to see? It all starts with data, and lots of it.
Put simply: the more granular data you have on your users, the more likely your success at personalization will be. So how much data is enough? That’s a tricky question to answer, but you probably have much more of it than you think, and certainly enough to start adding some value.
Let’s take the scenario of a brand that’s had an e-commerce website for 5 years. They have not implemented any 3rd party behavior tracking tool, and have simply been capturing the basic order data at checkout. At the very least, they’ll have the following data on each of their customers:
- Products purchased
- Order frequency
- Average order value
- Frequency of promotions
- Payment methods used
This is actually quite a bit of data to go on. It’s enough to start segmenting their customers into groups that they can start to target with personalized content. They know what types of products each person buys, how often, how much they like to spend, and whether they respond to promotions. At the very least, the brand can target specific customer segments with targeted banners or promotions based on the products they’ve previously purchased.
Personalization is really about segmenting customers based on their likes and behaviors, then providing relevant content targeted to those segments. A segment can be big, containing tens of thousands of users, or small, even containing a single user. The more you segment, the more targeted your personalization will be. The more data and attributes you have on a customer, the more accurate your segmentation will be.
The digital age requires omnichannel data
Traditionally, brands have focused on gathering user data in a very siloed way within each channel. They may understand their website customers, but don’t necessarily link that up with data gathered across other channels. The key to effective customer data management is understanding that customers are likely to interact with a brand across multiple touch-points, providing different clues to their behavior with each interaction. These channels include websites, mobile apps, in-store, multiple social media channels, live chats, or the telephone.
In this digital age, each of these touch-points provide a brand with a wealth of different data on the customer, but the trick is to bring it together. Once you combine the data, you can start to intelligently segment your customers based on very rich and accurate data set, allowing you to personalize your content effectively.
Let’s look at a scenario of a typical customer of a fashion brand who shops with that brand both online and in-store. The consumer may buy from the brand’s website a few times a year, which gives the brand a certain amount of data. The customer is reticent to buy more expensive items online, and therefore will go into store to purchase those. In addition, their customer is a frequent user of various social media channels, and often comments on Instagram and tweets regularly on fashion subjects, sometimes even mentioning the brand directly. Once or twice the consumer has called the brand’s customer service phone line and has used their live-chat service a handful of times to get style advice.
All of the above touch-points can provide the brand with vital data about that customer. Though some social media posts made by the customer don’t mention the brand directly, this data is still relevant to the brand. Each of the touch-points give the brand a certain view of the customer, but not a holistic view. Imagine how powerful personalization would be if all of this data were pulled together into one unified customer view.
Invest in the future
It’s at this point that the brand needs to invest in some clever technology. They need a CRM platform that gathers data from multiple channels and that has tools to allow the brand to segment users on any data point. They need a platform that can monitor social media channels and pick up on references to their brand or related terms and link those social media profiles up with their customers. They need to invest in technology that can help users interact digitally with the brand while they are in store.
The great news is that this technology is available now. CRM platforms can help brands link their consumer data from across all platforms and allow them to powerfully segment their customers. In-store beacon technology can help identify users when they visit physical stores, while digital signage, in-store tablet, and kiosk technology can encourage an in-store customer to interact digitally with the brand, allowing them to gather more data on that customer.
This excellent (although slightly terrifying) presentation illustrates how big data and personalization has been used to devastating effect during key political events. Facebook is one of the biggest users of user profiling and personalization in the world. All advertising and promoted content you see on Facebook is highly personalized based on every single interaction you have with the platform. The power of this is not in the actual delivery of the personalized content, it is in how the company understands, profiles and segments each of their users.
Of course, once you have the data, you need to use it well, but how you do that is for another article on another day. The important thing to take away is that without good customer data to work from, personalization is likely to fail.