A major component of the Big Data revolution at most companies has been putting customer data to work. While there’s a lot to be said for dealing with the basics, such as sales tracking and website visitor logging, you may also want to explore some of the more unique ideas that yield valuable insights. Here are 5 ways businesses are using customer data to create value.
Customer-Led Algorithms
Especially for companies that allow customers to create personalized items, a major step to consider is creating a customer-led algorithm. This entails:
- Making customers aware of their role in shaping the algorithm
- Providing them with the tools needed to interact efficiently with the system
- Creating a feedback loop of customer interactions and machine learning
Suppose you run an apparel company and your online store allows customers to create individualized designs. You can use the algorithm to track a slew of different features from each sale, including colors, sizes, and materials.
Beyond that, you can also use machine learning and vision systems to recognize designs and patterns. For example, you might spot a trend from customers who are focused on a specific set of memes. This information can then be used to create a new line of items or targeted marketing content.
Sharing Data Back to Customers
Collecting data without providing value to its originators can feel like bad form. Worse, customers often get upset when they fully comprehend just how much personal data a company such as Facebook or Twitter is using. This is seen as an act of taking without returning value.
Sharing data back to customers not only fixes the sense that companies are free riders, but it also provides a new source of content and engagement. For example, Pantone publishes two reports a year showing color trends in the fashion world, such as this one from Spring 2020. Not only does this allow Pantone to continue to assert its place as an industry leader and authority, but the reports give customers something to play with, inspire new ideas, and foster discussion.
Targeting Social Influencers
You likely already have a budget for doing social media work. A major question, however, revolves around how you can get the most bang for your buck. Many businesses use social media network graphs to identify specific influencers. Some individuals and businesses are networked to others in a way that drives opinions.
Notably, not all influencers have massive followings. Instead, the best influencers are often the folks who get the ball rolling on trending conversations. A well-designed system can identify who among your customers starts those conversations, allowing you to focus early marketing interactions with those parties. The next time you need to do a marketing roll-out, you’ll have a list of who ought to be prioritized.
Results Matching
Anyone who has used Netflix has experienced one of the more robust examples of how results can be tied to customer profiles. The streaming giant uses customer data to generate profiles, and a machine learning system regularly recompiles this information. Netflix can identify which genres people like, and it can also determine whether someone would prefer a long- or short-form program.
This allows the company to satisfy customers based on their taste and preferences without constantly harassing them for input. A user simply logs in to the system and is presented with numerous curated suggestions for what they should consider watching.
Spotting Customer Problems
Many companies lose customers due to a negative experience without first giving the firm a chance to improve or resolve the issue. Analyzing large amounts of customer data can provide insights about when customers are at the brink of leaving. Customer service professionals can then touch base with these individuals to learn about their situation.
If there is a specific problem that hasn’t been addressed, it can be flagged and fixed. You can also use this data to structure incentives aimed at keeping the customer on board.
Conclusion
It’s important to see customer data as more than just sales numbers and web traffic. Every piece of customer data is an opportunity to return value to individual consumer and the larger public. Bringing an adventurous approach to dealing with customer data can significantly differentiate your business from competitors as well as improve existing operations.
