When segmentation fails do you pivot to a new one?

A few months back this is what I wrote about economic value add for business vs. consumer segments while writing about price of LED bulbs,

Here is a case study done by US Department of Energy for LED bulbs. The initial price is almost twice as much as traditional lighting systems. While consumer segments most likely are not willing to pay twice the price for LED, business segments are. That is if you show them the value.

For instance, you and I may not mind changing light-bulbs every year because our opportunity cost is $0. But for businesses there are real costs associated with maintenance. Every bulb change avoided is not only savings in bulb cost but savings in maintenance costs.  If you add these all up, despite the high initial cost, the LED systems  deliver 9% in total cost savings over the lifetime.

Then I went on to show the economic value add from switching to LED bulbs

It seemed no brainer to start with the business segment that had real costs and savings (and budget to spend),  show them value using hard numbers and gain adoption. So did Cree, the maker of LED bulbs, think. Cree based their strategy on a similar analysis that pointed to increased adoption by businesses because of energy and labor cost savings from switching to LED bulbs.

As it turns out their segmentation strategy did not work out and they decided to shift focus from business segment to consumer segment,

the company is making an about-face. Durham, N.C.-based Cree is putting out a new line of bulbs built around light-emitting diodes, or LEDs, for the masses in hopes that greater use by consumers will eventually affect the choices made at their offices

Why did their initial segmentation fail to pan out? There are two main reasons I see,

1. Value Waterfall – As someone who defined value waterfall, even I failed to take this into account while I did the economic value add math for LED bulbs. Despite the real value there are several aggravating factors like cost of doing business, trust discount, switching costs, etc. that knocked down perceived value.
2. Pricing Model – The LED bulbs are priced twice as much as incandescent bulbs and deliver their value over long period of time.  That is the LED pricing captures value upfront while delivering customers value over time. A better model for businesses would have been a subscription pricing model based on usage. Cree needed monetization model innovation to go along with their product innovation.

I do not believe their segmentation failed nor do I believe they need to switch from business to consumers. But Cree believes,

The bet is that light bulbs might follow the same trajectory as touch-screen smartphones, whereby consumers grew comfortable with the technology at home and then insisted on having it available at work.

While that worked for phones that we use everywhere and at work and think of it as part of our self the same logic does not extend to light bulbs what are simply part of the environment.  Besides how can they get consumers to pay twice the price when the economic value add math does not add up and the fact that it does not have aspects of conspicuous consumption like a smartphone does?

I wrote recently how monetization model innovations follow segmentation. Cree’s segmentation was not wrong it is their product positioning and monetization model that need to be realigned to the business segment.

When your well thought out initial segmentation fails it does not mean you chose wrong and you must switch to a completely new one. Segmentation is a strategy and changing it is not like a product pivot. And there is no guarantee you will succeed with the new segment if you commit the same mistakes you committed with targeting, positioning and pricing with the first segment.

How do you choose your segment and what do you do when your product fails to get traction?

The Simplest of all Business Models

If you want to use Wifi at Pete’s Coffee & Tea you will have to buy something first.  At the counter they give you a code to use, that allows you about an hour of surfing time.

In many local coffee stores you technically have to buy something but once you do, you can stay parked in their tables for hours without buying anything. In Pete’s bigger competitor, Starbucks coffee, it is the similar unlimited free access plus access to premium extras like The Wall Street Journal.

Coffee shops complain about those who occupy tables for hours at a stretch, buy little or nothing and mooch on their bandwidth as well as electricity. Customers who do spend money at coffee shop and need good connectivity for an hour or two complain about the poor speed and difficulty in finding tables near outlets. General customers (who hire the coffee shop for, coffee) complain about the crowd and lack of seats to simply sit and enjoy their brew or have a conversation.

Free Wifi became a popular perk for coffee shops, restaurants and hotels to attract customers and keep them in their shops. If the customers chose your business over others because of free Wifi, you win. If the customers stay because of free wifi and continue to spend during their stay, you win. You have successfully used free wifi as lead generation tactic and customer retention  tool. (Freemium?). For instance, Panera bread saw its sales increase by 15% when they introduced free wifi.

On the other hand, what is free to customers, is not so to businesses. There are costs of operation (making sure there is enough capacity) and opportunity costs (both for the money spent on their big pipe broadband and the moochers). When everyone else offers free wifi it becomes difficult for a business to either stop offering it or start charging for it. Add to this customer dissatisfaction from providing poor internet service.

Look at where we are in the discussion. We are not talking about the compelling value proposition a coffee shop (or a restaurant) offers but talking about a perk. Let us not forget the primary job these businesses wanted customers to hire them for. If customers’ choice is made based on secondary and tertiary factors, the primary value proposition has become irrelevant. If a business fears their customers will walk next door for free wifi they are admitting that their product is an easily replaceable commodity.

That is a bigger problem they ignore while fretting about wifi costs. In focusing on free wifi as lead-gen activity they ignored the core customer segment they started with and the customer jobs they hoped to serve. While some may call free wifi (and Freemium?) as business model innovation, this is essentially losing sight of customer needs and your core competence.

If the customers didn’t hire your coffee shop for coffee, should you tie your business model to selling coffee? That is an incongruence between value creation and value capture.

On the other hand your strategy – to serve the most amazing coffee – need not be fixed. You can see the customer shift and decide your strategy is to serve those customers who have a connectivity need and are not satisfied with existing alternatives. You recognize customer issues with poor speeds in free wifi places and provide reliable speeds as differentiated feature. In such a case you cease being a coffee shop and become a workspace provider. And guess what, you now can charge for that value delivered.

The business model is back in sync with value capture matched to value creation.

That is exactly what is happening in Russia’s Clock Cafe.

“You don’t have to pay for coffee or tea or cookies. You should pay for time, and time costs — I hope — [are] not that expensive.”

And their target segment? Students and business folks who hire them for connectivity and hence pay for the value they get.  Nicely done. However, I think they fixed one mistake but introduced another – making coffee free. There really is no reason for them to offer free coffee, especially the premium kind they claim they deliver,

We have cappuccino, latte, espresso, Americano, and our coffee is not the cheap one

They are committing the flip side of free wifi at coffee shop mistake. Sooner or later they will run into the free wifi problem in reverse. Why bother with coffee or why not charge for it? Especially if the customers didn’t hire you for coffee?

When it comes to business strategy, starting with customer needs and choosing the ones that you can serve better than others remains the best approach. And when it comes to business models, charging for value you deliver remains the simplest of all approaches.

What is your strategy? What is your business model?

4 Ways You Can Put Google Customer Surveys To Work Today

As I previously wrote, Google Customer Surveys is a true business model innovation. It helps publishers unlock value from their digital assets and enables market researchers reach new audience they otherwise would not have found. I expressed my reservations on their positioning in my previous article

But I do not get what they mean by, “look for correlations between questions” and definitely don’t get, “pull out hypotheses”. It is us, the decision makers,who make the hypothesis in the hypothesis testing. We are paid to make better hypotheses that are worthy of testing.

Since I wrote that article, their Product Manager emailed to say they removed their statement on, “pull out hypothesis”.

This is a limited tool with ability to ask just one question and no way to ensure that the same user will answer multiple questions for doing customer level analysis.

There is one more item which is their minimum sample size. You cannot order anything less than 1000 samples.

Despite these reservations I see Google Customer Surveys as an effective tool for product/brand managers, researchers and small businesses for these purposes:

1. Aided Recall:  Present them a choice of different brands ask them how many of these they recognize.
When you are trying to get very quick and high level data on customer awareness or preference of your brand, this is a great tool. The results are especially actionable when you get extreme results like no one knows about you.
If you are trying to find which brand they recognize the most then you can do that as well with different question type. However, due to its question format limitation, Google Customer Surveys cannot help with Unaided recall.

2. Finding Consideration Set: Present them a choice of different brands and ask them how many will they consider buying for solving a particular need. This is similar to Aided Recall but the question is more focused. You are not simply asking about awareness but whether your brand makes it into their consideration set.

3. Brand Association: Present them an image or a statement and ask them to pick a tag-line or brand they believe goes with it. Another variation of this question is asking them to associate your brand with an unrelated field. A typical example is, “if our brand were a movie actor, who will it be”.

Ability to use images is a very powerful feature. It creates many different opportunities. For example for testing your advertising copy or the images you use in your collateral. It is better to poll your audience whether the image you used looks more like a bean bag or boxing glove before you launch your expensive advertising campaign.

4. Consumer Behavior Research: This is a whole class of hypothesis testing you can do with Google Customer Surveys. While it is not a tool for A/B split testing, you can use it test your hypothesis on customer preferences or their susceptibility to anchors and other nudges. Before collecting results you need to specify a reasonable hypothesis that is worth testing. When you collect data you can test for statistical significance using Chi-square test to validate your hypothesis. Do keep in mind that sometimes data can fit more than one hypotheses

There is however a big limitation because of the length of questions you can ask (as you see in the third option in the image on the left).

There you have it. A tool with limitations but is effective for specific areas. It opens up new ways to collect data and test when none existed before.

A corollary for this post would be cases where you should not use this tool. That includes finding price customers are willing to pay or asking them about how important a single feature is. You have to wait for another post for the reasons.

Google Customer Surveys – True Business Model Innovation, But

Summary:Great business model innovation that points to the future of unbundled pricing. But is Google customer survey an effective marketing research tool? Do not cancel SurveyGizmo subscription yet.

Google’s new service, Customer Surveys, is truly a business model innovation. It unlocks value by creating a three sided market:

1. Content creators who want to monetize their content in an unbundled fashion (charge per article, charge per access etc)
2. Readers who want access to paid content without having to subscribe for entire content or muddle through micro-payments (pay per access)
3. Brands seeking customer insights, willing to pay for it but have been unable to find a reliable or cheaper way to get this

When readers want to access premium content they can get it by answering a question posed by one of the brands instead of paying for access. Brands create surveys using Google customer surveys and pay per use input.

Google charges brands 10 cents per response, pays 5 cents to the content creators and keeps the rest for enabling this three sided market.

Business model is nothing but value creation and value capture. Business model innovation means innovation in value creation, capture or both. By adding a third side with its own value creation and capture Google has created an innovative three way exchange to orchestrate the business model.
This also addresses the problem with unbundled pricing, mostly operational challenges with micro-payments and metering.

But I cannot help but notice severe sloppiness in their product and messaging.

Sample Size recommendation: Google recommends brands to sign up for 1500 responses. Their reason, “recommended for statistical significance”.
Statistical significance has no meaning for surveys unless you are doing hypothesis testing. When brands are trying to find out which diaper bag feature is important, they are not doing hypothesis testing.

What they likely mean is Confidence Interval (or margin of error at a certain confidence level). What is the margin of error, at 95% confidence level? With 1500 samples, assuming 200 million as the population size it is 2.5%. But you do not need that precise value given you already have sampling bias by opting for Google Customer Surveys. Most would do well with just 5% margin of error which requires only 385 responses or 10% which requires only 97 responses.

Recommending 1500 responses is at best a deliberate pricing anchor, at worst an error.

If they really mean hypothesis testing, one can use a survey tool for that, but it is not coming through in the rest of their messaging which is all about response collection. The 1500 responses suggestion is still questionable. For most statistical hypothesis testing 385 samples are enough (Rethinking Data Analysis published in the International Journal of Marketing Research, Vol 52, Issue 1).

Survey of one question at a time: Brands can create surveys that have multiple questions in them but respondents will only see one question at any given time.
Google says,

With Google Consumer Surveys, you can run multi-question surveys by asking people one question at a time. This results in higher response rates (~40% compared with an industry standard of 0.1 – 2%) and more accurate answers.

It is not a fair comparison regarding response rate. Besides we cannot ignore the fact that the response may be just a mindless mouse click by the reader anxious to get to their article. For the same reason they cannot claim , “more accurate”.

Do not cancel your SurveyGizmo subscription yet. There is a reason why marketing researchers carefully craft a multiple question survey. They want to get responses on a per user basis, run factor analysis, segment the data using cluster analysis or run some regression analysis between survey variables.

Google says,

The system will automatically look for correlations between questions and pull out hypotheses.

I am willing to believe there is a way for them to “collate” (not correlate as they say) the responses to multiple questions of same survey by each user and present as one unified response set. If you can string together responses to multiple questions on a per user basis you can do all the statistical analysis I mentioned above.<;

But I do not get what they mean by, “look for correlations between questions” and definitely don’t get, “pull out hypotheses”. It is us, the decision makers,who make the hypothesis in the hypothesis testing. We are paid to make better hypotheses that are worthy of testing.

If we accept the phrase, “pull out hypotheses”, to be true then it really means we need yet another data collection process (from a completely different source) to test the hypotheses they pulled out for us. Because you cannot use the very data you used to form a hypothesis to test it as well.

Net-Net, an elegant business model innovation with severe execution errors.

The Pricing Story You Likely Did Not Read About

You likely read the many opinions about Netflix pricing. This isn’t about that. This is about something boring, something you do not think about much (even though your safety depends on it) and something you buy only every five years or so.  It is highly utilitarian consumption but does have hedonistic and conspicuous aspects to it.

Tires!

Specifically Goodyear’s tire pricing case study. I am not breaking news for you, it was in the news. Most of you likely missed it. It is not about Goodyear using Customer engagement, Co-creation, Business Model Innovation, Social Media, Gamification, Product Innovation, Superior Design,Decoy pricing, Viral campaign etc. So none of the Gurus wrote their opinion on it.

The story has none of the popular components to it. It is very dull. It is just a story about how Goodyear  relied on first principles of strategic marketing to increase revenue and most importantly increase profit.

Here is the link, if you do not have access you should find a way to get it.

The headline is,  Goodyear increased revenue by 25% with just 2% increase in number of tires sold. Most strikingly its turned a profit of $143 million from a previous year loss of $19 million (I did not check income statement to see if there were any one time charges).

How did they do it? None of the quick fix recipes. It simply started with their segmentation. Until an year ago, Goodyear sold more tires to auto makers than they did to customers. The problem with auto makers is tire is yet another component that adds to their cost. They want the cheapest possible tire both in terms of quality and the price they are willing to pay.

Goodyear stated,

the key to its turnaround has been concentrating on fewer but higher priced products targeted more toward consumers than auto makers.

The impact on its pricing?

Four years ago, almost 40% of the tires it produced were low-end tires retailing for about $60 apiece.

The average likely pulled down by even lower wholesale prices to car manufacturers.

With their new strategy to focus on consumer segment (rather than auto makers)

Almost 75% of its tires now sell for $130 and up.

Note that the price change started with their customer segments. The product mix did not change until they made the strategic choice about customer segment to serve.

Knowing the current customer mix and making a strategic decision to change it to drive revenue and profit is not innovative. But given that most have forgotten the first principles of business in favor of the fads of the time, following first principles would soon be called innovative.

That is is a pricing story worth telling many times.

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Note: Not all the profit increase can be attributed to segmentation strategy change alone. They did some operational efficiency changes (another boring act) and negotiated deal with union.