Using Data-Driven Personalization to Create Insightful Offers

Our recent survey found marketers believe personalization leads to success, but about half say their approach is only somewhat successful. The reason: not turning the data into actions. Our websites are capturing all kinds of data, more than we expect or know what to do with sometimes.  It can be overwhelming to look at column after column of your customer engagement data and the abilities of your marketing tools. Making changes usually requires more than one team member to strategize, sign off, implement, monitor and analyze reporting to glean new insights and achieve success. 

However, the expectation for personalization is only increasing as we enter a new decade. I expect to see my first name in email body copy and subject lines, I expect to receive age-relevant ads or gender leaning emails - those are the checkboxes I told the company about myself. Yet, those were questions they asked so they could segment me. That isn’t engagement based personalization. None of those tags really explain how I, as a customer or prospect, have engaged with a company’s product. Sure a company can do its best to guess and guide me along, but actually acting upon the data collected is how brands need to shift customer experiences. 

The survey found that the most important types of marketing data are website activity, transaction activity and campaign activity. The idea of activity is important here - not just understanding customers’ or prospects' activities, but turning the data about those activities into marketing activities. One of my favorite examples of using engagement based communications has actually been around a long time - the abandoned cart message. Anyone who has “window-shopped” on sites like Staples or Amazon and added items to their checkout cart has likely received those “you have items in your cart” email messages. This is the exact logic that should be utilized when sending your customers through a journey. 

What have they done? Browsed. 

What do we want them to do? Come back and buy our product. 

How do we get them back? Incentivize them with their selected items in an email message and make it easy to access the cart page. 

How do we get them to click purchase? Have a welcome back message using website pop-ups and create a seamless checkout process. 

Even if a customer doesn’t come back to purchase those items, that is information captured. You now have their preferences. If you categorize or use tags to help segment engagement data, you have ways of creating a message in the future (think when it goes on sale) or showing a customer similar products. This makes it so not every record needs your personal attention, but you can segment based on different categories. You also have the ability to see email engagement in this scenario. Did they open the email? If not, restructure your subject lines or the time of day when you send those abandoned cart messages.

Turn this same logic into how you message your database. What has the record done? If nothing, continue lighter touch, educational messages introducing your brand through email, SMS, text, pop-up messages, chatbots, etc… If you have a record who is clicking different pages on your website or downloading materials, mark that action using your segmentation columns. It can be a simple true/false, or you can go a step further and assign the asset a customer engaged with as its own column value. For instance, if I was browsing orange waterproof parkas on the Patagonia website, they’d know I have an interest in orange products, waterproof gear and cold-weather garments. Each of these categories could put a different filter on me. An email message could have a subject line such as “Marnie, see new raincoats for spring” with a preheader that says “Yes, we even have raincoats in orange!”  This goes beyond just “Marnie, we have new spring items for you.” It shows that a brand is acting upon engagement data to better tailor a personal message to its users. The subject line on the backend would look something like this “{First_Name}, see new {Product_Preference} for spring”. It’s taking my actions on the website and turning them into personalized messages that are relevant to me. 

Strategies need to stop relying on what worked before: Data extends to marketing metrics -- not just data on customers, but data on how your personalization marketing efforts are resonating. Having tools in your stack that allow you to analyze and pivot are critical. What does the approval process look like to sign off on a new strategy? How flexible is your team and your tools to implement new strategies? It’s important to gage results often, but are you taking stock of competitors’ messages or gathering industry baseline metrics? What do email open rates look like for you now and what should they look like in six months? How large is your database now, and how much should it increase by next year? It’s important to keep quarterly reminders on your calendar to review and analyze all automated messaging. 

This is where we can get lazy. Having tools that allow for flexible changes is imperative if you want to keep optimization top of mind. Personalization trends are only going to get more aggressive in the future. Additionally, marketers should get in the habit of auditing and documenting all communication channels. At any point in time, they should know what messages are popping up or triggering. This will make sure brand messaging is always accounted for and aligns with changing priorities and strategies. 

Personalization can lead to success, but it requires strategy, effort, data and analysis. As we develop and excel in our roles, we can forget how to speak humanly and personally to our audience. 

Download our new report for more stats on how marketers are doing with personalizing the customer experience.