Spend a minute with anyone working in interactive and you're bound to hear at least a vague reference to the long tail -- a theory put forward by Chris Anderson in his book by the same name. But for all the talk, interactive is still grappling with two fundamental questions: What does the long tail really mean, and is it something that you should be pursuing?
The long tail has different meanings whether you are in manufacturing or advertising. But it basically refers to the idea that a small group of product offerings or keyword lists covers the majority of the market opportunity. It's really the 80/20 rule. If you only have to make a certain number of products to cover 80 percent of the market, it would require a lot more effort to go after that remaining 20 percent. Often that 20 percent is too much to justify the costs, begging the question: is it worth it?
The same holds true for keywords. It's likely that a small number of keywords bring in 80 percent of your traffic or sales. But what about the remaining 20 percent?
Before automation on both sides, that portion of the market was impossible to go after efficiently. Now that automation makes it possible, the question remains: should you?
This article will speak to the product side. Later, I will tackle the other side of the equation -- SEM.
The long tail reality
The internet was going to enable thousands, no, tens of thousands of niche offerings. And those offerings would be so highly-customized to speak to consumers' need states that you'd be optimizing and reaching the maximum market opportunity. The reality is something different. There are arguments on both sides as to the value, but it is often a perceptive conclusion. It all depends on what data set you're looking at, and whether you are the big brand looking to expand product offerings or the small brand concentrating on a niche.
There was an intriguing article in the Harvard Business Review about whether you should invest in the long tail. It's a great article, but it draws some strange conclusions as to next steps. The article speaks to what is essentially the 80/20 rule, using various published studies. Theory is great and all, and citing other studies is often quite impressive to bolster your point, as this article did. However, the devil is in the details.
Example beyond the data
First, the article draws several of its conclusions based solely on the sales data. Tsk, tsk. "But Sean X, data doesn't lie!" No, it tends not to, but it does not tell the whole story, or even remotely deal with the dynamics of intent that drive those purchases -- the purchase cycle. It is like looking at a myopic funnel of the process and extrapolating conclusions. And that is a dangerous road to walk.
What that article misses, is the "phenomenom of choice." I will provide several examples:
A well known 24-hour grocery store found that even though it incurred 20 percent of its expenses from 10 p.m. to 6 a.m., it only made 6 percent of its sales during that period. It decided to change its hours from 24 hours per day to closed from 10 p.m. to 6 a.m. Their logic was that they would save 20 percent of overhead for only a 6 percent profit cut. But sales actually dropped 30 percent for a net loss of 10 percent. Why? The phenomenon of choice. By changing from the ultimate convenience, 24/7, the perception in the consumers' minds was that the store was less convenient. "Were they open 'till 9 or 10? I don't know. I'm going to the other place."
Just looking at sales data captures the end of the process, the result. It does not deal with the dynamics of what generated it. Logic based on data, often has illogical outcomes.
Campbell's Soup often has half an aisle in the supermarket dedicated to its red and white cans. However, Cream of Mushroom and Tomato account for a significant slice of the total profits of that aisle. Should Campbell's just make fewer soups, use less shelf space, and get rid of the dogs? Of course not. They understand that when the consumer sees a swath of red and white cans, Campbell's is soup. They peruse and then choose their Cream of Mushroom, Broccoli Cheese and Tomato soups. The phenomenon of choice.
The long tail often wags the short tail. Be careful to study what the impact will be with consumers on the perception of your brand, and not just sales data.
Herman Miller advertised its Resolve furniture line, even though it accounted for a small fraction of its sales at the time. Consumers drawn in by the design aesthetic of that line of products often made more practical choices when it came right down to it. But it was that line that brought them in the door. Without it they were going to be out of the buyers' consideration set. And that is the difference. If you're just looking at the "sales" data, you're not measuring the dynamics of consumer intent. And that is the major flaw in the HBR article criticizing the long tail.
What gets people in the door is often not what they eventually buy. Product differentiation is often key in consumer choice. Sexy products sell the less attractive and less expensive ones.
Even though 90 percent of the movies you rent at Netflix are blockbusters, the phenomenon of choice is why you are a member. If they only carried the top 100 titles would you join? No, because you want the choice, even if you're not going to use it. If they scaled back just to the blockbusters, the consumers would abandon the service. What the article does correctly point out is that resource allocation of the long tail is key.
The phenomenon of choice drives membership. Be careful when eliminating choice if you are a membership based service.
So what should you do if you are a manufacturer or brand?
When considering the long tail, manufacturers and brands should ask the following questions:
- What are the resources required to make niche products or carry them in your catalog?
- Will those niche products bring consumers in the door, even though they'll buy more conventional offerings from you?
- Do those long tail products provide a marketable point-of-differentiation in your competitive set that can be leveraged in advertising?
- What's the loss in not making them? Not the hard numbers, but equating consumer shift in mindset because of their elimination.
The "hard" numbers in sales data sets are often a driving force behind many decisions in business. They are a known quantity. Myopic managers often use hard data as their decision making tool because even if the result is negative they can point to hard justifications for the decisions. It is the result of corporate structures that do not reward success but do punish failure -- a review structure where as long as no one has anything negative to say the person gets promoted. Elevation through mediocrity. That mentality is the hallmark of marketers coming from a consulting background who do not understand the fuzzier "gut" decisions made by seasoned marketing professionals.
However, that gut decision is not really a gut decision at all, it is usually based on consumer research, psychographic studies, survey data, focus groups, observation and a deeper understanding of the dynamics of consumer intent. The problem is that most of the time, decisions based on that data do not have the concrete numbers to fall back on. It's fuzzy. That so-called marketers' instinct, the ability to consistently call it right on those decisions, comes from something else -- knowledge and experience. Marketers who operate in that manner often get the comments "How did you know?" when a program is a success. It can't be taught in schools; it has to be learned in the real world. But what makes them that good is often intangible.
What can you do if you are stuck in such an organization? Well, if your company is run by CFO types, not much. You're kind of, what's the word I'm looking for? Oh yeah, "screwed." Hard data is their friend. A way to approach that mentality is with as much data as you can muster. For example, you might run Netpromoter score data if you have an online presence. That data, although based on consumer opinions, can often be tied directly to sales fluctuations. Also, econometric modeling has come a long way. There are several companies who can help provide all the inputs that affect the sales data, instead of just myopically concentrating on the sales output.
Marketers who operate with instinct, and a more thorough understanding of the dynamics of consumer intent, understand that it is the future trends that are important. Those who base decisions only on concrete data are only looking at the past, hoping for a repeat performance. And the market is often not dynamic.
In the end, don't believe what the experts who write the books say, don't believe what a competitor's data says, don't even believe anything I write here. Your company is unique. It has challenges that are based on its people, its manufacturing process and its corporate structure. But what if a competitor in your space is getting better traction, making more money and growing even though you think their process is flawed -- they're just lucky, right? No, they're thinking the same thing about you. Only difference is, they're right.
Sean X Cummings is a marketing specialist.