1. Focus on MicroconversionsA common mistake companies make is to measure all customer interaction (marketing efforts, site changes, etc.) by revenue. This foolishly assumes that all interactions can (or should) be measured against each other to find the "best".
Avoid this pitfall by understanding the nuances of the customer lifecycle. After creating a map of customer needs, big data can identify all the customer touch points in each phase of the purchase process. Focus on what each interaction should directly influence. Begin to have a real discussion with customers by helping them reach the next step or overcome the next hurdle.
2. Personas … or notA high-level view of customer interactions is useful, but the natural next step is to go to town with segmentation analysis. Experiment with the different ways to categorize your customers: by products purchased, by phase in the purchase process, by geography, by demographics, by preferred contact methods, etc. The most useful segmentations will vary by company.
Some companies may define personas: categories of customers that have certain needs or outlooks or preferences. For other companies the way to interact with customers will be based less on who they are and more on what they are trying to achieve right then. This type of categorization should guide how a company interacts with individual customers, what it offers them and how it contacts them.
3. Unique HabitsBig data provides unprecedented power to understand each customer's unique trends or habits. No matter how accurate different categorizations may be, there will be deviations. These deviations provide an opportunity if a company that is paying attention. If a customer buys something unusual or starts to interact with a company differently it might represent a willingness to expand their relationship with the company. An alert company could respond by sending offers for new categories of products or experiment with new mediums. This level of responsiveness is what customers appreciate as long as it feels organic.
In the end, there is no single formula for a company to personalize their offerings to each customer. But big data provides tools we have never had before to treat customers as individuals and anticipate their needs in a natural way.
This is part 3 of a five-part series on big data and web analytics.
- Part 1: Big data and web analytics
- Part 2: Big data uncovers macro trends
- Part 3: Big data can provide more effective personalization
- Part 4: Big data can align company goals with customer needs
- Part 5: Big data introduces new risks