Customer-link analytics helps marketers understand influence

One of the hottest trends in analytics for CSPs is social-network analysis. As we’ve all learned, it only takes one highly influential person to severely damage — or improve — your business reputation. And it can happen in the blink of an eye. Wouldn’t you like to know who your biggest influencers are?

To understand this, CSPs need a very large matrix that scores the connectedness between subscribers. Consider that there are about 250 million subscribers in the U.S. alone; potentially, any two users could be connected. In practice, this matrix is sparsely populated, of course. That’s because any one user is directly connected to only a tiny fraction of other users in a market.

It can take many hours to populate the matrix and score the relationships between users if you rely on traditional methods. Because of time constraints, most CSPs don’t score communities very often.

Unfortunately, your business reputation could be scarred indefinitely within a matter of hours. On the other hand, if you could use that time to connect with your most influential customers, you might see a striking turn of events.

High-performance analytics allows you to run customer-link analyses faster, more often and with much larger data sets of information that are accurate and continuously updated. As a result you’ll have a much clearer picture of the influence individuals have within their social groups, helping you turn their influence into a positive factor in how others view your company and services. The bottom line just might be higher retention rates and improved return from customer acquisition efforts.

Real-time analysis of online and TV consumer behaviors can boost revenue

In the past the measurement of television audiences was based on very small sample sizes. There was no way to deeply analyze or connect behaviors, and many questions were left unanswered.

With the new generation of video set-top boxes and digital video recorders (DVRs), the potential is here for CSPs to capture every click of the remote. Collecting and uploading this data creates a huge repository of actual viewing data from individual consumers. Effectively analyzing the data can address three business objectives for video service providers:

• predict a change in customer behavior that indicates potential churn or up-sell opportunities;
• improve program scheduling and pricing based on actual viewership;
• maximize advertising revenue through accurate, real-time targeting.

Clearly, these opportunities are attractive. So why haven’t more video service providers taken advantage of them?

For one, it’s extremely complex at a technical level to coordinate all of the data coming from multiple devices. Set-top boxes were designed to collect and send information to the provider indicating whether or not they’re functioning properly, not to collect programming information. Plus, vendors have not fully standardized the formats they use to collect viewing data.

All the same, some CSPs are likely to adopt high-performance analytical methods to evaluate consumer behavior data in the near future. That will allow them to cater advertising, programming and pricing to the unique needs of specific individuals.

For example, if you know enough details about your dad’s viewing habits, you can probably determine if he’s likely to leave the room during a commercial break. If he is, you have the chance to figure out if there are certain ads that actually strike his interest. Or you can wait and run those ads near the end of a show that he really loves — he’s less likely to head to the kitchen for a snack at that point in the broadcast.

With this approach you potentially reduce the number of ads you run for specific viewers while at the same time raising the ads’ relevance. You’ll also know if a customer isn’t watching much anymore — which signals potential churn and alerts you that it’s time to make that customer a very good offer.

To get there you’ll need a lot of data to build long-term profiles that are constantly updated by real-time behavior. High-performance analytics gives you the capabilities to effectively manage this complex process.