Increase customer loyalty through individual personalization


PHOTO: Franki Chamaki / Unsplash


Using zero and first-party data to personalize digital marketing campaigns across all platforms can increase customer loyalty by guiding potential or existing customers through their buying journey. It starts with collecting data about your customers in a confidentiality-compliant manner, which requires their consent to the data collection. This consent is best obtained with the promise of a better customer experience.

Data collection can be centralized through a brand’s own data warehouse or hosted in a cloud-based warehouse, or businesses can otherwise purchase a specially designed customer data platform.

From the perspective of Tom Strachan, senior vice president of marketing sales at Lytics, a provider of personalized marketing technology, the key is to develop a consistent understanding of who your customers are behaviorally and demographically. “Behavioral data can infer a lot more from customers, but it’s something organizations need to organize,” he said. “This is where data analytics and machine learning (ML) can come in, to help understand your customers’ preferences. “

Strachen said that with the increasing volumes of data that businesses face – often across multiple channels – the use of data science and ML tools is critical to successfully organizing email clicks. , website visits and other metrics.

Nathan Richter, vice president of strategy and ideas at DynamicYield, said zero-party data collection can be used more effectively by engaging with customers through digital channels in a conversational way, such as a quiz that helps guide purchasing decisions. “This immediate engagement with the customer helps focus on what you need to know about them, and then you have the flexibility to run the site by focusing on what they told you, as well as keeping that information. long term, ”he said. noted.

Associated article: 6 ways AI-powered personalization improves the customer experience

Using AI to meet higher customer expectations

According to Marylin Montoya, vice president of marketing at AB Tasty, customers today have very high expectations, so the closer you get to your customers, the more you can anticipate their needs. “They want experiences that are tailored to them and things that are available to them when they want it,” she said. “It’s about finding that balance between privacy and personalization, getting to know that customer and the energy you put into those efforts. “

She recommends starting with anonymous data, which brands can use to try to personalize experiences. “We have invested in machine learning to analyze anonymous browsing behavior in an attempt to understand the intent of this customer,” she explained. “You don’t need to collect a ton of data, but you can try general customization – it’s a way to start. “

Montoya said many companies want to go 1: 1 right away before considering the complexities of structuring data and investing in copy and promotion, which can create problems. “Just start out using some background data and some background personality, and once you start to understand the client better, you can invest in longer-term types of strategies,” she said. “The key is not to overuse the data just because you can. You should consider which channel you are on and what information the customer needs to make that purchase. The key here, Montoya said, is to make sure the personalization brings the person’s psychology into the equation.

“You need to look at customer behavior and make sure that if you’re personalizing, you’re doing it in a way that it’s relevant to that person, like using geolocation tools or buying behavior models,” that can change depending on what device they’re using, ”she explained.

Richter said AI, ML, decision engines, and modeling can help get the most out of customer data by extracting information that wouldn’t be seen by looking at the data in the normal way. “This is where the industry is most technologically focused and where a lot of brands are turning,” he said. “It’s about creating new opportunities from this data set. Automation is the industry’s goosebumps.

Related article: Personalization: At the intersection of data and content

Collect data and create associations

The graph databases added by Strachan are ideal for collecting data and associating features with a primary attribute. “I can take your behavioral data and all the content and products that you watch on your favorite brands and then link it to you,” he said. “What products are you looking at in real time and creating a product taxonomy so you can understand the affinities. It helps people understand the relationships between data points and the strength of those relationships.

Strachan shares Montoya’s view that it’s important for brands to understand which channels the individual is active in, what machine learning and data science can also help – users who tend to click on them. emails on Monday, for example. “Most marketing groups are set up by channel – ads, mobile, web, email – and they work in their own tool from their own set of data,” he said. “This 360-degree customer profile becomes important because they may not click on emails but on the mobile app. You must therefore know on which channels these customers are located. You need to collect all of this data in one central location so that you can figure it out. From there, brands can send offers when that person is most active or, based on their knowledge of their behavior, which channel they prefer.

Richter noted that ultimately brands need to validate whether these 1: 1 strategies are more effective for the consumer. “You have to do the A / B tests, determine your purchases and validate decisions is something that brands struggle with,” he said. “This is where the art of personalized marketing comes in; become more intuitive, more personalized, more valuable to the consumer.

Joseph P. Harris