Big Data is Improving Personalization Models for Scalable Marketing Campaigns

My friend from Seattle had the opportunity to visit the Gartner Customer 360 Summit a couple of years ago. A lot of topics were covered, but one that stuck out the most to them was the growing emphasis on personalization. Many brands are creating personalized online content to better reach their customers. It wouldn’t be possible without recent advances in big data.

One recent poll found that nine out of ten marketers believe that personalization is the future. This should come as no surprise, because 48% of customers spend more with brands that deliver a personalized web experience. Nearly 80% of customers state that they will share their personal data with a brand that promises a more personalized mobile experience.

Brands Finally Recognize the Benefits of Web Personalization

Louis Columbus, the Director for Global Cloud Product Management at Ingram Cloud, is one of the foremost authorities on marketing applications of big data. Columbus has provided some interesting insights that marketers should be aware of. His research shows that big data can help in the following ways:

• Reducing customer acquisition costs
• Maximizing customer lifetime value
• Improving conversion rates
• Improving customer engagement

There are a number of ways that marketers can use big data to offer a better web experience for their users. Moosejaw Mountaineering uses customer browsing and sales data to offer incentives and personalized product recommendations.

“We use our knowledge of the customer to determine who gets a catalogue, direct mail, and what type of email they will be receiving,” Dan Pingree, VP of Marketing at Moosejaw, stated in an 2014 interview with Retail TouchPoints. “This is important because it helps those channels perform at a higher level and helps us better satisfy and retain our customers… We reflect this knowledge in our marketing, which helps customer more easily find what they are looking for. This helps us better retain repeat customers.”

Many other brands have adopted similar strategies. Target, Victoria’s Secret and Kohl’s are among the leading retailers that have discovered the benefits of using big data for personalized marketing campaigns.

However, personalization isn’t a silver bullet for marketers. As with any marketing strategy, they need to test many variables before they find the best approach. They will find that some personalization strategies work much better than others. They will also need to decide what types of data is most valuable.

Columbus stated that marketers primarily focus on collecting data on products. They use this data to optimize their supply-chain models, identify equilibrium price points and choose the most profitable products to sell. Marketers have only recently begun to recognize the benefits of collecting data on their customers and using it to create personalized content. Companies like Group Mobile can help them create personalized mobile experiences as well.

However, there are drawbacks to using big data to create personalized marketing campaigns. One of the biggest concerns is customer trust. Many customers have stated that they have felt uncomfortable when Facebook and Google advertisers use their personal data to create custom ads. They feel like they are being spied on and exploited, which is why advertisers such as Valpak try to make sure that data is used in a nonintrusive way.

According to Thomas Data, personalization works better when brands full of these three principles:

• Get their customers consent for displaying personalized content
• Acquire customer data from trusted sources
• Are fully transparent about their data partnerships

Keep in mind that most customers are happy to have a personalized web experience, but marketers can’t take them by surprise and act intrusively.

Advances in Big Data Will Make Personalization Easier

Many marketers believe that personalization is the next stage of marketing. None of it would be possible without major advances in big data. Brands that improve their big data infrastructure will have many more opportunities to reach their customers in the future.