Here are three examples of how organizations are using clickstream data to understand each customer’s engagement with their business and then to respond to that customer proactively based on their behavior. In other words, these are examples of how organizations are acting on their customer big data to drive more revenues.
1. Move free users to paying customers
Many organizations offer prospects a freemium or free trial as a marketing strategy. But the point of such an offering is, of course, to convert the users to paying customers. Clickstream big data can help with that.
For instance, consider an online service provider for real estate brokers who had the following problem:
- They spent a lot of money and did a lot of work to capture the interest of prospects and move them down their acquisition funnel to the point of beginning a free trial.
- Then, they lost touch with them. It was like the customer had entered a black box. Some customers popped out the other end ready to buy. Others lost interest and never bought. They were relying on the free trial alone to sell itself.
This company decided to shine a light into the black box and get an understanding of what its customers were doing in the free trial. They started collecting information like how often real estate agents were visiting, how much time they were spending in their solution, and what actions the agents were doing. With this data they could tell if the users were just browsing or posting their listings and promoting them through the application. They could tell if the customer was using more advanced functionality or just the basics.
This data is like a gold mine for their sales and marketing teams as it enables them to target different users/customers appropriately. Now:
- Sales reaches out to the high engaged, high value customers.
Marketing sends emails to users who have not visited in a while encouraging them to come back.
Marketing can message users in-context to help them complete their setup and use the more advanced functionality.
Another organization with whom we work, has close to a million users on a very low price monthly plan. These are consumers, individuals who are occasionally using their solution. Some of these users are candidates for an upsell to a higher priced solution but most are not.
How best to tell the difference and communicate effectively? Sending everyone an email about an upsell is close to spam and didn't result in the best conversion rates.
Using clickstream data, they now identify the best candidates for the upsell. These are the people who are using the tool often, using the power features, and whose usage is really increasing. This allows for a targeted email to the right prospects for an upsell.
With the availability of in-context messaging, new options open up. Right in the application, as the power users are using it, they can message the users with a promotion to consider upgrading to the higher priced solution.
In a SAAS or subscription business, churn rates are an important factor in success, profitability, and valuation. The same techniques we have been discussing can be used in this area as well.
Too often, an organization's customers feels like that organization communicates with them either:
- Too infrequently: Of course, I hear from you now at renewal time…the last time I heard from you was at the last renewal!
- Too frequently: You again. Stop spamming me.
Because the organization doesn’t understand them, it can’t communicate effectively with them. Not sure if they plan to stay or leave, the organization isn't sure what to do.
Clickstream level data lets them understand this better and act to make a difference.
Consider a project management company, with whom we work, that calculates an engagement score for each customer. This score is based on their behavior in the system:
- Is this customer visiting and for how long?
- Is this customer creating new projects, updating current ones, adding tasks, using advanced features like measuring time?
- How many projects does this customer have? tasks? users?
The project management company uses this data to
- Keep in touch with customers proactively over the year with targeted emails that talk about areas of the product this customer isn’t using or could use better
- Understand 3 months before renewal whether this customer is at risk or not and proactively engage if they are at risk
Getting Started using Customer Big Data for Customer Success
So, how can you get started making use of clickstream level big data to understand and respond to your customers?
- Next, you watch as data about your customers and their engagement with your application starts flowing in. Set up some filter rules to find customers who haven't visited in the past week, are at step 4 in a funnel, have/haven't used a particular key feature, are of a certain role, industry, company size, etc....
- Then, decide how you want to respond: in person, by email, or with messages based on this behavior, right in your site or app.
With just these steps, you can use customer big data to drive more revenues.