Provoke. Geoff Tuff

CHAPTER 1 Patterns from the Past

      “1.75%? Why would I care?” asked the senior executive as he flippantly tossed the PowerPoint page onto his conference table, put his foot on the table, leaned back in his chair, and, yes, stuck his hand into his pants like Al Bundy in the 1990s sitcom Married with Children.

      Steve and his colleague exchanged a knowing glance. They had worked together for 15 years and by that point they basically shared a brain, which, at that point, was thinking: “Is this guy for real?”

      They were in his lavish office, sitting at his conference table. Steve noticed the golf trophies, pictures with celebrities, and large and expensive desk. The office screamed, “I'm successful!”

      It was 2009 and, given the difficult economic climate, Steve and his colleague were being especially aggressive in getting out to meet new executives. They had done some work for a large, diversified media and communications company, creating a segmentation of consumer behavior in its industry. Their client, pleased with the work, was looking to present it at an upcoming industry conference and wanted to get some reactions from executives at peer companies – hence the reason they were sitting in Al Bundy's office.

The work they were sharing included a detailed segmentation of the consumer landscape for communications services like Internet, phone, video/television packages, and security. They had surveyed thousands of customers about their behaviors and actions. The survey revealed the typical and expected results: when people got married or had families, their Internet and video usage dramatically changed from when they were single. Expenditure on things like pay-per-view and other channels tended to be higher among this group. With more devices in the house, they also were willing to pay for higher Internet bandwidth.

      This wasn't news. Companies in this space knew and loved these customers. They paid their bills on time, they didn't move, and as a result they didn't “churn.” And, back in 2009, they probably had a landline, too. Therefore, if you successfully acquired one of these customers, you were likely to retain them, leading to a steady, predictable stream of revenue.

      At the other end of the spectrum were the singles. They typically lived in an apartment and had more focused communications needs. This was a group that tended to select the most basic Internet and television packages. Sometimes this choice was driven by personal preference (think people who like to read at night). But sometimes this was driven by affordability, where having lots of channels could be expensive. You could predict the reasons for this choice based on income levels (typically tied to specific geographic locations) and whether the home was rented or owned. Some singles with higher disposable income bought a more comprehensive communications package, but it typically included just video and Internet; even in 2009, this group didn't want a landline – a mobile phone was just fine for them. These singles, perhaps because of their income or preferences, were willing to spend more on faster Internet speeds and specialty channels.

Because of the high capital intensity of the communications and entertainment distribution market, players in this industry wanted to win all of these customers. It wasn't economically viable to focus on just one segment, so Steve's work was designed to help companies customize their product, pricing, and marketing messages to better target the needs of each of these groups. For instance, if you had an area that overindexed on owned homes, that was a sign that there were probably a lot of families with kids, and you'd advertise a comprehensive package. If you were targeting an urban area with a lot of apartment renters, you'd make different choices.

      None of this was particularly earth-shattering in 2009. The work was solid, but the patterns were generally predictable to experienced executives in the space.

      Except for one small anomaly.

      A seemingly inconsequential group of customers – that 1.75% that the exec had dismissed – was exhibiting some unique behaviors that made it challenging to assign them to one of the larger segments. When segmenting an industry, it's preferential to get to between four and eight meaningful segments of the marketplace that are small enough to be unique but large enough to merit individual focus. But, from an analytical perspective, the 1.75% just didn't fit into any segment.

These were younger people, so Steve and his team tried to type them to the segment with other single people. But they didn't really fit. They had lower income, so the team tried to group them with the budget-conscious single group, but they didn't pick the lowest-cost Internet. They actually wanted high Internet speeds. They tried to bundle them with the higher-income single people, but those folks didn't buy TV packages. Most of the time they would pick the most basic TV package, and many of them didn't even have a TV package at all. If they could buy “just Internet,” they would – but at high speeds. If their Internet provider required them to also purchase television or phone, they might purchase Internet elsewhere, sometimes getting a cellular hotspot (previously you could just use your mobile phone as a hotspot) instead of a wired home connection.

When Steve and his team further investigated this group and tried to understand whether they were just uninterested in video content, they found the opposite. This cohort of singles was quite interested in video content, but they weren't watching traditional network programming. They watched short-form videos on the then-new YouTube. They watched snippets of online video and they subscribed to the new streaming service offered by Netflix, introduced a year earlier, which had only around 1,000 titles and set a limit of 18 hours of streaming per month, a far cry from the Netflix that has become both a noun and a verb.¹

      Intrigued, Steve and his team dug deeper. What they found was that this behavior was rooted in preferences, not cost: this small group simply preferred to consume content in this way. The segment wanted to watch the shows they wanted to watch when they wanted to watch them. They wanted smaller, bite-sized chunks of content. They wanted it ad-free (but, given that they were budget constrained, they would tolerate ads if that helped make it more affordable). And they were pretty agile about finding ways to view their favorite shows online without paying for them, if it could be done.

      In short, they consumed content in this way not because it was cheaper but because it was better – although the fact that it was also cheaper made it a zero-trade-off change for consumers.

But the executive wasn't buying it. He seemed more interested in discrediting the research methodology than the findings.