Personalized marketing is a technique that allows brands to provide consumers with unique, customized content. The strategy is built on the combination of several elements: Data collected on individual users, the ability to apply that data to serve each visitor, and an automated technology solution that can accomplish both at scale. Personalized marketing is now a crucial aspect of delivering a thorough and successful campaign.
In order to create successful campaigns, marketers must understand the inner workings of the solution itself. Becoming familiar with the technology that drives personalized marketing will help you better align your strategy with your personalization engine.
Let’s dive into the mechanics and key components of a personalized marketing solution.
Personalized Marketing Has Evolved
The use of personalized marketing has now reached an all-time high, and consumer expectations have grown in response. In fact, 58 percent of customers say they want a more personalized experience and the same percent also feel that it would better their overall user experience. In order to keep up, brands are working hard to deliver a more personalized experience through customized homepages, dynamic content, and unique discounts and email offers.
Whereas personalized marketing used to be considered an emerging tactic, it is now an absolute must. According to Infosys, 74 percent of customers feel frustrated when website content is not personalized. In 2015, 78 percent of CMOs said they felt that custom content was the future of marketing. And now the future is here. Not only is this form of personalization nice for brands to have, but it is also to be expected.
The Mechanics of a Personalized Marketing Solution
Now that we’ve established that personalized marketing is a brand imperative, let’s delve into how the technology behind a personalization engine actually works. Personalization engines utilize data from user profiles or from tracking anonymous user behavior. This personal information is then layered with second or third rounds of additional data such as real-time behavior, previous purchases, geolocation, third party data, and more. The decisioning engine uses all of those data layers to make a choice about which available content options would be the best match for each visitor. This is where machine learning algorithms kick in to perform a more granular analysis: By optimizing for each visitor, instead of by segments, the machine can deliver decisions at a more individualized level than what marketers would be able to accomplish manually. This allows marketers to offer a more personalized marketing experience at scale.
So, how does machine learning perform that more granular analysis? Machine learning involves the ability of computers to “learn” from past experiences and observations by leveraging predictive programming and algorithms to find patterns that rule-based programming can’t. Over time, as the machine tests its theories about what will work for different visitors, it uses the results of each experience to confirm or deny those theories so that it can develop more nuance in its decisioning. As it gathers more and more data about what works and what doesn’t, the machine gets “smarter” while also remaining agile enough to detect sudden changes and adjust accordingly much faster than a team of marketers can. While a good engine should also give you the option to create as many rules as you wish manually, an assist from machine learning will yield better results and deliver that truly personalized experience you’re looking for.
You also might be wondering how raw data translates to a personalized user experience. Gigster explains that the data first goes through a cleaning process, followed by normalization and matrix factorization. Once it is combined with the custom code, it is run through the personalization engine. This is how each individual user is able to encounter a unique customized experience.
Of course, having a personalization strategy team in place to oversee the technology will put you at an advantage. Even with a well-thought out plan and an advanced technology, things can go wrong. A solid team that is dedicated to ensuring that the process is running smoothly is just smart business.
Aligning a Solution with Your Personalized Marketing Strategy
Bringing a solution into your marketing strategy can help to ensure you are delivering the sharpest possible decisions for each user. If you aren’t already, you should begin taking the necessary steps to incorporate a solution that is right for your brand.
If you are an ecommerce platform or sell products online, your strategy will pair well with a solution that can help you recommend relevant products in a more appealing manner. Personalized product recommendations engage customers and give them guidance that reflects their context and history with the brand, helping to keep your customers out of the 71 percent who say they feel frustrated with impersonal shopping experiences.
A brand’s approach to product recommendations should be part of a larger personalization strategy, ensuring that each customized element across channels can be combined into one seamless experience for the user.
Examples of Personalized Marketing Technology in Action
It is always helpful to see a concept in action. Here are a few examples of how personalized marketing technology has made a positive impact on a brand.
Office Depot Saw ROI to the Tune of $6.9 Million
When office supply retailer Office Depot wanted to expand their personalized marketing efforts, they decided they needed a solution that worked for everyone. An engine that only catered to known customers was not an option, so they were looking for one that worked for known and anonymous customers.
When they began using the Monetate Intelligent Personalization Engine, they were able to begin aggregating and evaluating customer data instantaneously—and that real-time data aggregation translated to unique real-time experiences for each customer. As a result of emphasizing or deemphasizing content depending on the user, Office Depot saw a $6.9 million increase in revenue in just 4 months.
Frontgate Wanted to Maximize CTR
Home and furniture brand Frontgate wanted to maximize click-throughs to product detail pages. They realized that if they were able to drive traffic to these pages via endcaps, customers would be driven down the sales funnel, increasing conversions—but they knew they needed to get the details right.
Once the retailer began using Monetate’s Majority Fit algorithm, they discovered that the optimal location for product recommendations on category pages was at the top of the page. As the algorithm gained increasing confidence in that decision, it began gradually allocating a higher percentage of traffic to that split. By leaving the Majority Fit algorithm running, the brand found that it enabled them to adjust to ongoing changes in user behavior. As a result of this tactic, Frontgate saw an almost immediate 10% uptick in their click-through rate.
Waitrose & Partners Catered to Customers Old and New
A popular feature of grocery retailer Waitrose & Partners’ site is the recipe page. The brand shares these recipes under various themes such as Quick and Easy, Healthy Food, or Comfort Food. Although these categories do appeal to shoppers overall, each section caters to a different persona. Choosing the right content for web viewers became a challenge for Waitrose & Partners, so they teamed up with Monetate to implement a strategy to drive engagement on these pages.
Monetate’s solution utilized AI and machine learning algorithms to feature the optimal recipe for each customer. When the experience was implemented on the recipes page, the team saw a 6.21 percent lift. After that initial success, the Waitrose & Partners team deployed this experience onto the homepage, with the result of increasing engagement with the content by nearly 67 percent.
Understanding the mechanics that drive a personalized marketing solution can help you look at your own strategy in a new light. From the data you’re collecting to the customers you’re trying to reach, looking at your personalized marketing strategy through the lens of a personalization engine will bring you the results you’ve been after.
If you would like more information on Monetate’s personalization offerings, head over to the Monetate Intelligent Personalization Engine page. Or, to speak with an expert, feel free to contact us today.