In most aspects of our life, there is too much information coming toward us.  We need services that help us to filter, prioritize, and focus on what’s important.  

This is as true for information about our customers as it is for news or email.   

Customer Engagement scoring enables you to know more about your customers while at the same time prioritizing and focusing your efforts.  

Manual Curation

One way to filter and organize in order to focus is to have people do it manually for us.  For  example, for news and general content:

  • Fred Wilson talked about ways people curate streams of content on twitter (lists), Etsy (favorites), and Tumblr (tag pages). 
  • Some of the people I follow on Twitter and the blogs that I read fulfill this function for me.  These people sort through the massive amount of information available in a particular subject area and post the highlights.  
  • An administrative assistant filters meeting requests for an executive

For information about customers, we do the same.  There are too many customers and too much information coming in about each customer for employees to personally digest and make use of it all.

  • A sales person puts the most important customer quotes out of a 2-hour meeting into the CRM system.
  • After two days onsite, a user interaction designer describes 5 different 10 minutes intervals on the day of the target user. 
  • After a 30 minute call, a customer support representative writes up a ticket with a few notes. 

Manual curation is very important, and can be very effective.   But, a company’s ability to manually process information about its customers scales at best linearly with the number of customer-facing employees.    If your only way to organize the data is through manual work, then you will arbitrarily limit the information you collect.

Algorithmic Curation

Some of the leading web companies have been very successful at capturing huge amounts of data and building algorithms that “curate” that data to filter and prioritize it:

  • Amazon makes suggestions on what to buy based on what other people have bought(collaborative filtering)
  • Google gives you the best search results by using applying its PageRank algorithms to   among other things the authority of links to each page.
  • Facebook decides what content to put in your newsfeed using its EdgeRank algorithm
  • Google prioritizes your inbox
  • LinkedIn, Facebook, and Twitter suggest people that you may know or want to follow

These companies are capturing more data than a person would be able to handle and they are able to leverage their algorithms to better prioritize what you should see.

This is one way to think about what Apptegic provides you.  We enable you to capture much more information about your customers and how they are interacting with you.  We then leverage our algorithms to suggest to you the customers most in need of your attention in a variety of categories, for example:   

  • Best hope of converting from free to paid
  • Most at risk of churn
  • Ready for an upsell
  • Needs more training.  

You could think of us as your own Customer Engagement Rank algorithm, tailored to your customer data, helping you filter and focus on the right customers at the right time.