Churn is a measure of customers leaving a subscription-based service over time. In this post, we use Ethersource to
- demonstrate real-time monitoring of churn-propensity related to telecom services;
- characterize customer churn by means of annoyance, uncertainty, change, and negativity;
- identify and extract, in real time, the source documents provoking the churn for a service (in this particular case, a rumour surrounding Sprint Nextel’s service).
A challenging question in subscription-based industry segments is: As a service provider, how do I detect that a churn-provoking event is taking place, in a timely manner permitting me to act on that information, in order to short-circuit the situation (as opposed to finding it out at the end of the fiscal Quarter)?
Consider as back-drop to this post the age old adage “A Lost Customer is Not a Potential Customer”, and its relative pertaining to the higher cost associated with gaining a new customer, than it is to retain an existing one: “A Bird in the Hand”. As a service provider operating in a competitive landscape, you are concerned with those of your customers who are on the verge of terminating their subscription with you in favor of one of your competitors. Hence, the question starting off the post. What’s even more pressing is that since churn and retention is (approximately) a zero-sum game, you need to be aware of churn information related to your competitors when deciding on, and executing your contingency plans.
We use Ethersource to take a look at the five largest mobile network operators in the United States with respect to the relative manifestation in English social media of the churn components, introduced below, during August and September 2011. The operators are (rank and numbers from wikipedia): Verizon Wireless (107.7M subscribers; 35% of the subscribers among the five operators compared), AT&T Mobility (100.7M; 32%), Sprint Nextel (51.1M; 16%), T-Mobile USA (33.73M; 11%), and TracFone Wireless (17.75M; 6%).
Ethersource facilitates the detection of peaks in churn component signals, and allows its user to identify and thus to directly engage the individuals airing the concerns that underlie such peaks. As an operator, you can use this opportunity to raise your visibility in order to make yourself available, allowing for the user to contact you at will; directly approach individual users, or; launch and follow up campaigns targeted at a select group of users.
We charactersize customer churn in terms of a number of core components, all related to how people express themselves in relation to a service provider with respect to annoyance, uncertainty, change, and negativity. Increasing or fluctuating signal levels for any of these components, or combinations thereof, may constitute a cause for concern.
First off, let’s see how the number of subscribers per operator relates to the on-line chatter for the given time period. Image 1 shows the relative amount of chatter for the operators in September. The only operator generating an on-line buzz larger than its proportion in terms of subscribers is Sprint Nextel.
Image 1: The relative number of on-line chatter for the five mobile network operators in September 2011.
Given the disproportional attention awarded them, Sprint is what we’ll focus on. We use the time series, as they are produced by Ethersource with respect to the churn components and the companies outlined above, in an as-it-happens manner to identify a situation in September in which Sprint, but not its competitors, may see an increase in customer churn. Note that this approach allows for continuous monitoring of events as they take place; there is no need to wait until after-the-fact to carry out a proper analysis.
The images below show expressions of uncertainty (Image 2), annoyance (Image 3), change (Image 4), and negativity (Image 4) towards the five mobile network operators. We are monitoring all the time series depicted below simultaneously, looking for occasions when the values for Sprint Nextel are higher than those of its competitors. A high value for a combination of the churn components, including as many components as possible, warrants a closer inspection. Looking at the images below, there is one date in particular that is interesting: September 16, 2011. It is the only date on which all churn components exhibit higher values for Sprint than they do for any of its competitors. (Note that the graphs are timed to Stockholm time, and so the start of the event is really on September 15 in the timezones hosting Sprint.)
Image 2: Expressions of uncertainty. Red circles mark dates in September when values for Sprint Nextel are higher than for its competitors.
Image 3: Expressions of annoyance. Red circles mark dates in September when values for Sprint Nextel are higher than for its competitors.
Image 4: Expressions of change. Red circles mark dates in September when values for Sprint Nextel are higher than for its competitors.
Image 5: Expressions of negativity. Red circles mark dates in September when values for Sprint Nextel are higher than for its competitors.
What happened to Sprint on September 16?
Rumors of iPhone 5 happened to Sprint. The rumors had it that Sprint would be the exclusive reseller of the new Apple handset.
By using Ethersource, we can inspect the expressions in the social media underlying the signals, and thus make sure we understand exactly what is going on. It turns out that people express themselves in relation to
- uncertainty about whether the Sprint network can handle the traffic generated by the new iPhone: “Can Sprint handle iPhone traffic?”
- annoyance about rumored alterations to contracts as a result of the introduction of the new handset: “Sprint Readies To Remove Even More Customer Incentives.”
- change of the abovementioned contracts: “Sprint puts an end to the Premier loyalty program”
- negativity that the new handset might have on Sprint’s services: “What Sprint users should find alarming is his acknowledgement that the iPhone could potentially hurt the company in the near term because of the higher subsidies involved…”.
The quotes above are taken verbatim from top-ranked sources in Ethersource. Image 6 below shows a partial screenshot of Ethersource with a number of sources ranked according to their uncertainty value, early on September 16.
Image 6: A partial screen shot of Ethersource, containing the top five sources (cloaked) contributing to the uncertainty score at the point in time labelled "Z" in the red oval.
So, the rumors of a possible advantage for Sprint, that is, the new iPhone 5 handset from Apple, turns out not to be all that positively received.
We’re sure Sprint was all over this particular event; it is used here merely as a case study to show some of the capabilities of Ethersource, when working with a polarity set-up beyond that of the ordinary positive-negative dichotomy. In fact, it would’ve been very hard to use negativity only to identify the rumor of the iPhone 5 set out on September 16 as something extraordinary for Sprint.