America introduced the 1-800 number in 1966. It was a great product for companies who were willing to take the risk and cost of making a phone call off the hands of their potential customers. Anything that lowers the barrier to trial is usually a good thing.

It was such a good thing that soon we were running out of 7-digit numbers to follow the toll-free prefix. In 1996 the second toll free number was added: 1-888. It only took two years to add the third: 1-877, and two years after that the fourth: 1-866. By 2014 we have added 855 and 844 to the mix, and reserved five more for future use (833, 822, 880, 887, 889). That’s a lot of toll free options.

The problem is that many of those potential customers don’t understand that these new 1-8XX numbers are the same as the traditional 1-800 numbers. People know that 1-800 = free, but they are less clear that 1-844 = free. This confusion is understandable. Most of the 1-8XX numbers are NOT free. 1-877 will get you a toll-free line, 1-878 will dial someone in Pennsylvania. Call 1-876 and you end up in Jamaica. Hope you have an international calling plan.

People don’t have the mindshare to remember which numbers are toll free and which are not (For your personal use: All the toll-free numbers (for now) are double digits – 888, 877, 866, etc. And the double digits that aren’t toll free either will be in the future or are just unassigned).

Because people aren’t sure if a non-800 number is toll free or not, they may be less likely to pick up the phone. Maybe they go online to verify it’s toll free, but more likely they just use it as a reason to not take action. It’s really easy to choose not to take action on just about anything. This is just one more example why you want to minimize the excuses your potential customers could have.

At least that’s the theory.

What happens in practice.

We asked our media buying agency to run a test where we ran the same ads with different phone numbers – so we could see the impact on phone calls with different 8XX options while everything else remained the same. Turns out we didn’t need to run the test, because they already had. They tested 1-800 vs different 1-8XX numbers on seven different TV networks. Then they divided the numbers of calls they received by the amount they spent on each stations. Here is what they found:

On average the cost per call was almost THREE TIMES more expensive when using a 8XX number over a 800 number.

So why not always use 800?

The problem is that there were companies that got their first. The whole reason we have 8XX numbers is we ran out of 800 numbers. But think about that a little bit. There are 7-digits after the area code, with 10 options for each digit. That means there are 10 million 1-800 numbers. Have we really used them all? Kind of.

Just like the domain name rush in the early aughts, there was a 800# rush. Now they are all owned by someone. Most of the owners are not using them themselves. Instead they will rent you numbers for a price (usually a monthly fee plus a cost per minute when it is used). An 800 number will cost you about 10x the price per minute as a 8XX number.

So figuring out which type of number to use is a math exercise depending on the number and average length of your expected calls, and the cost of your media. If you are running an ad on TV though, it’s pretty clear that your overall costs will be lower by paying the 10x premium to use the traditional 1-800 numbers.

Depending on where you draw the line between sales and marketing, one could say marketing has been around forever. In the interests of brevity, we can start the story of Marketing in the early 20^th century. The first real ‘go’ at marketing was the discovery that repetition of a consistent brand was important. Companies like Coke and P&G figured it out early on and used whatever media existed to get their consistent brands in front of consumers to win share of mind.

People had theories on what worked, but mostly they were guessing. The famous quote, “I know 50% of my advertising is working, I just don’t know which half” could easily describe marketing from the very beginning. It was obvious  the consumer goods companies that had extensive advertising campaigns were more successful than the ones that did not, but it was very unclear which specific advertising activities were driving the impact.

The basic problem is that brand advertising impact is so thinly spread out. When you see a TV commercial for Coke you don’t jump up and buy a Coke right away. You likely don’t even jump up and drink a Coke right away. But somewhere in the back of your mind you increase neurological connections to the Coke brand and sometime in the future you may be slightly more influenced to choose Coke over another option. But because that “slight influence” happened “sometime” in the future, it’s practically impossible for the advertiser to figure out that that specific spot caused you to go over the edge that specific time. Even the person being influenced doesn’t know (so surveys are a waste of time).

The obvious impact combined with lack of data and difficulty with any real measurement created demand for people who could explain what was going on. The best of these ‘experts’ were master storytellers who could spin a yarn. They told stories based on psychological experiments or customer surveys or sometimes just anecdotes spun into narratives. With nothing better to go on people took their advice. Maybe marketing got better and maybe it didn’t. It was very hard to tell anyway. But it didn’t matter too much, since overall it was working. People were buying what brands were selling. Who cares if it was fully optimized?

By the 1950s the US had Madison Avenue. The storytelling just kept getting better, even if the science was not. “Better” tools followed. NPS scores were ‘scientific’ measures of customer satisfaction. Media mix models used multiple regression to tell you the relative value of different marketing channels. Conjoint Analysis and Max-Diff helped quantify customer surveys to figure out what customers ‘latent’ values really were. Products started being positioned. Blue Oceans were discovered.

The issue was it was hard, if not impossible, to prove any of this stuff actually improved impact. It definitely made people feel better about their decisions – it was SCIENCE – but it was science without proper A/B testing to measure real results. These new quantitative marketers were just like the ad men of the 1950s – they just had better storytelling tools.

(And the best part is they were generally ‘selling’ to marketers with no quantitative intuition themselves. So it was easy to pull out a black box and ‘reveal’ the final decision.)

Enter Real Science

Within all this hocus-pocus there was one part of marketing that was using real science. It was the least sexy and maybe the least desirable career in marketing: Direct Mail Marketing.

DM Marketing involved sending direct mail to thousands or millions of homes asking people to mail something back, or call a number, and buy something. The response rates you could imagine were terrible: 3% would be a fantastic campaign. But the beauty was the costs were relatively low (at least compared to television) and you could measure changes with (almost) absolute certainty.

You could send out ten different versions of a mailer – different colors, different copy, different envelopes – whatever changes you wanted to make – and send them all to the same group of people (randomly divided into ten sub-groups – one for each version). Then you could measure the response rate for each version. If Version A got a 3% response rate and Version B got a 2% response rate, you know the changes you made from B to A got you an extra 1%. But you don’t need to stop there. You can keep iterating the changes to find out what works and what doesn’t. You can change offers. You can change prices. You can change the gender of the call center person who answers the phone. Anything to want.

And each time you test a change you learn something. Not the learnings that came from the witch-doctor marketing, but real learnings you could replicate. When you tried to replicate it and it failed, you learned something then too and you would add it to your quiver.

Over time people become experts in DM Marketing. They had run so many tests that they had intuition on what worked and what didn’t, so they didn’t need to test everything anymore (but they could). They were the first real marketing scientists.

Taking DM to the Store

The next big advance in marketing was Loyalty Programs. DM Marketing was great, but it only existed in a dark corner of the marketing world. Even when DM Marketing made it to TV (with Infomercials and Direct-response advertising) it was still hidden away in weird time slots in the middle of the day or the middle of the night. But Loyalty let marketers use the techniques of DM Marketing with mainstream businesses.

With Loyalty Programs companies could track individual customers over time. Then they could begin to run experiments on the impact of changing things. What happens when you send someone a coupon? Do they buy more? Do they shift brands? Do they just move spending forward and reduce it later?

Before Loyalty Programs the answers to that question was just guess work. Now retailers could run real A/B tests and figure out the actual drivers of improved sales.

The problem was people forgot what the purpose of Loyalty Programs were. They got caught up on the name and started to think Loyalty Programs were designed to drive Loyalty. They ignored the data analytics and tests they could run, and instead just looked at numbers showing Loyalty Members spend more than non-Loyalty Members (It’s called Selection Effect, which I will expand on in another post). If you believe that getting someone to join a loyalty program gets them to spend more, then just getting people to join on its own creates value. Turns out that was wrong. If you look at all retailers that have Loyalty Programs and compare to those that don’t – the ones that don’t have had significantly better ROI and Market Cap improvement over time. Loyalty Programs on average destroy value.

Except when they don’t.

If you use them correctly – to turn your business into a smart DM-Marketing machine – Loyalty Programs can add a ton of value. It just turns out that most companies don’t use them that way.

Along Comes the Internet

In the early days it was hard to get people to buy on the internet. But the early leaders like the Jeffs Bezos and Skoll worked hard to change that. And then people started buying.

The best thing about the internet:

• Now every company has DM-Marketing data

The second best thing about the internet:

• Now DM Mailings are (basically) free.

Now you could run analysis on anything. Now instead of spending $1M to send a million pieces of mail, you could spend $1000 to send a billion emails. The ability to test went through the roof.

It took a while for the tools to do all this testing to be fully developed (Google Analytics didn’t launch until November 2005!), but now they are everywhere. All of a sudden everyone is a Direct Response Marketer whether they know it or not.

In general this is a good thing. A/B testing can teach you an awful lot that the Quantitative BS of the last century couldn’t. And we can measure those A/B tests on all sorts of sub-metrics: impressions, conversion rate, customer flow, multi-session tracking – just about any behavior you can imagine.

All of a sudden data is the easy part.

But with more data comes more responsibility.

We aren’t taking responsibility.

Instead the data-marketers compare their quantitative methods to the qualitative methods that came before and since they are convinced that what they are doing is ‘better’, what they are doing must be ‘right’.

Obviously we don’t need to figure out what color our website should be, all we have to do is A/B test it.

Obviously we don’t need to think about how to segment our customers, we will just do Big Data Analysis and it will spit out the segmentations we could never see with our naked eye.

Obviously this counter-intuitive fact must be right – it was proven in the data.

There are two problems with all this.

First, there is a difference between proof and Proof. Significant results are still wrong 5% of the time (and likely not important 50% of the time). When you are running Big-Data sized tests and trying to backward-infer results, this 5% gets really really important.

Second, just because we can do something, doesn’t mean we should. I’m not talking about ethics, I’m talking about impact. Personalization is great, but sometimes (usually) it is better to create a great product than personalize a crappy one. Data might help you make a better product, but only if you choose to spend your time trying to do that, instead of spending the time with the sexy new personalizing algorythm.

It’s great that marketing has moved away from qualitative BS. Now we need to resist the urge to deify anything that has math and algorythms behind it. Quantitative BS exists and it’s all around us.

In 2007 The Economist had a special briefing on business schools. Among other things they argues that ethics classes were becoming more important, and that the programs have more drinking than learning (and used a pub crawl at Wharton as an example). I wrote a letter that was lucky enough to by published a few issues later (Economist March 31st 2007, Letters). Here is the short letter:

SIR – The Walnut Walk (which you called the “Wharton Walk”) is much more of an occasion than you described. Students do not just visit “ten bars in a single night”. The revellers are required to wear suits above the waist and boxer shorts below while being stared at by passers-by. If that does not reduce the arrogance that leads to Enron-sized scandals, then I am not sure the trend towards ethics classes you reported will help.

Yesterday I wrote my second letter to the newspaper.

The article in question talked about how effective Big Data is at making many many small changes that add up to big effects. I generally disagree. Here was the letter:

SIR-

Schumpeter repeats the standard optimism around the latest management buzzword: “Big Data” (“Little things that mean a lot”, July 19^th, 2014). In my experience that optimism needs to be tempered by three often ignored drawbacks.

First, while Big Data may allow companies to target the last “20” of the 80/20, most companies have not yet finished with the 80. By going after Big Data they risk missing the core drivers of their company performance.

Second, when shooting for 1% improvements there is a significant risk of chasing noise. Normally a 95% chance of “Significance” is considered ‘real’, but it means there is a one-in-twenty chance your results will not be ‘true’. With the size of Big Data, thousands if not millions of interactions can be tested, leading to a plethora of false positives.

Finally, Schumpter makes the assumption that big effects can be achieved by layering on many tiny changes. This assumes the effects are additive. In practice most things in business interact with each other. These “interaction effects” can cause the 1% effects seen in isolation to change significantly in magnitude (or even direction). This can be overlooked when the effect is big, but when it is tiny you may find yourself optimizing for a world that doesn’t exist anymore.

Big Data is a wonderful marketing slogan, but most companies would be well served to invest in something more old fashioned. I call it Analytics.

I will expand on all three of those arguments going forward. In the meantime, if you haven’t already, you might want to check out my older post on the (lack of) value of Big Data.

I’m sure half of you (or more) have listened to the “Comcast call from Hell”. For those that haven’t (and can’t be bothered to click through and listen to an 18 minute painful phone call), basically here is what happened:

A guy tried to cancel his Comcast service. The agent on the line wouldn’t let him do it. No matter what the customer said, the agent would turn it around and stop the cancellation from going through.

It effectively turned into a conversation like this on repeat:

“Please cancel my service.”

“Why would you want to cancel your service? Comcast is awesome!”

Painful to listen to, and likely even more painful to experience.

And sorry. It’s my fault. At least indirectly.

I spent a good portion of my time at McKinsey specializing in how to set-up, manage, and optimize “Save Desks”.

What is a “Save Desk”?

A Save desk is a specialized call center that only takes calls from people who are planning to cancel their service.

Fifteen years ago Save Desks didn’t exist. Instead call center agents were generalists. They would handle new sign-ups, customer service calls, and process cancelations (and anything else that caused customers to call-in). The problem was that call center agents are very low paid but very expensive at the same time (since companies need so many of them). Trying to train a low-wage employee with high turn-over to do ALL the jobs was difficult. And it was even harder to measure them on the success of all those jobs. For customer service calls you wanted the customer to leave happy, and do it as efficiently as possible (i.e., customer satisfaction; handle time per call). For sales calls you wanted to incentivize sales (and you are likely ok if handle time was a little longer if it resulted in a sale). For cancelation calls you wanted to just keep the products the customer called in on.

When all the functions were done in one group, saving customers was lost completely. It was easy to measure sales. It was easy to measure handle time. But a lot harder to measure when you saved something – there was no way to know someone was calling to cancel unless the rep told you they were. If you let the rep make that decision themselves and then evaluated them on ‘save rate’, then it made sense for them to claim every call as a potential cancel. All of a sudden they would have 99% save rate.

And the skills were different. Being good at solving customer complaints was different from knowing the features and upsell offers you could make. And both were different than dealing with a customer who wanted to cancel.

The result was companies were terrible at saving canceling customers.

My job was to fix that.

Saving Customers

I traveled the world helping telecoms (just telecoms – my peers focused on cable companies so we weren’t sharing secrets with competitors) create save desks from scratch. And we had a system.

We would create a separate group that only took cancelation calls. The rest of the organization wasn’t allowed to cancel anything – they had to transfer customers who wanted to cancel to this special desk. That desk was given special training and coaching. They did daily huddles where they talked about different techniques. They were managed by specialist managers. For metrics we ignored handle time. Their core metric was their “save rate”. To calculate save rate we used some funky math:

{[Total calls handled] – [Total products cancelled]} / [Total calls handled]

So if you took 100 calls and half the calls canceled 2 products, you would have a 0% save rate. And yes, it could go negative.

In addition, for every call the agent was required to record what the reason for the cancel was. With that data we could measure the save rate based on reason. Turns out when someone is moving out of the country the save rate is basically zero for example (actually very negative since it’s all their products they are cancelling). But these numbers let us figure things out. We learned what the major reasons were people were canceling and what reasons we could save people and which reasons we couldn’t. We also learned which agents were good at saving which reasons, so we could learn from the best and reapply to everyone else. We could do targeted coaching: “Sarah, you are doing great, but when women from New York State call and try to cancel because they are moving to cell-phone only, your save rate is really low. Let’s go through some techniques that work really good in that situation.”

My favorite specific example was for the reason: “My son has his own line and now he’s moving to college, so we won’t need it anymore.” The save rate on that reason was close to zero.

So we solved it.

We created a special product that was only available at the save desk. It was only $5/month. It allowed you to have a separate line that only took inbound calls most of the time, but it could make outbound calls on weekends and holidays (including a 2 week time period around Christmas). It was designed so that when little Jonny came back from collage on over Thanksgiving he wouldn’t tie up the main house line. Save rate went from zero to almost 100%.

At one point when I was considering my next step after consulting I considered becoming a save desk specialist. My idea was to serve non-telecom/cable companies who had subscription products and help them set up their own save desks. Magazines and newspapers couldn’t afford McKinsey, but they could afford me if I went direct. I ended up going a different route with my career, but I still think that niche is viable for the right person.

Creating a save desk creates a ton of value for a company.

It can also piss a lot of customer off who just want to cancel their service. The problem is, from a company’s point of view, by the time you are ready to cancel, pissing some people off a little bit more is totally worth it if you can save 50% of the others. That’s a lot of revenue you hold on to.

So: While that Comcast agent was a little over the top (a lot over the top), he was just doing what I had incentivized him to do. Maybe next time I would put in a score around customer satisfaction. Or maybe just handle time. But if I did, I would want to test it. I’ll bet it would destroy value vs. just keeping it the way it is and dealing with fallout like this whirlwind every half-decade or so.

Earlier this week I posted my latest Marketing Is Easy chapter. Originally I planned Attribution to be one chapter, but as I wrote it I realized it was too big for one post – so it has been split in (at least) two.

Take a look and give me your thoughts. If there are big Attribution issues I’m missing let me know that too so I can incorporate into the next chapter.

Groupon and Expedia announced earlier this week that they are ending their co-branded relationship on Groupon Getaways by Expedia. Here is an article that covers it pretty well:

http://www.geekwire.com/2014/honeymoon-expedia-groupon-longer-co-branding-travel-deals/

This was inevitable. I know this because even though I initiated and helped negotiate the deal, I didn’t like the final version.

Was a bad deal inevitable? I don’t think so. Here is what I wish the deal had been:

1. Fully co-branded (Not Groupon Deals by Expedia, But Groupon/Expedia Deals)
2. Full partnership. 50/50 on everything
3. One deal per email (at least at the start)
4. One email a day

The reason for the first two should be obvious. It’s basically so both sides are inceted to grow the pie, instead of spending time and effort gaming who gets the bigger piece.

The second two might be less obvious if you haven’t read my post on the power of scarcity. When we launched Groupon Getaways the product was a dozen deals a week and have a weekly (opt-in) email sent out once a week featuring the deals. I was against it from the beginning. Here’s why:

When an email comes out every week (especially a Wednesday) it is not part of your ‘routine’. When you get an email every morning that is worth opening, you open it. It’s part of your morning routine. It was something Groupon mastered in the early days.

When you go to the market and talk to hotels and you need a dozen deals a week (or more – we were often going for two dozen). That means you need to convince them to offer a good deal. You might get a good deal, but you sure won’t get a great one. Why would you? As a hotel getting slotted into somewhere in the middle of an email is nice (it is going to millions of people) but it’s not nice enough for you to give up all your margin. And even if you would give up all your margin, you don’t have to – you can negotiate with the Groupon/Expedia team. The G/E team needed dozens of deals a week. They wanted deals that were ‘good enough’ so they could move on and get the next one. So that’s what they did.

The result: A lot of ‘okay’ deals that were loaded with limitations (only good Tuesday-Friday was a favorite for tourist destinations).

What would have happened if it had been one-deal a day (for five days a week) with an email every day?

I don’t know.

But here is my vision:

1. The E/G team goes out to hotels and tells them they are creating a product to offer smoking good deals. And only one hotel will be featured in each email. That email will go to 20 million or more people and will have 30%+ open rates who will consider your property
2. That should be enough to get some good deals. But it doesn’t stop there. Those deals are forced ranked from best to worst. The best deals are shown to customers first. If a hotel only offers a good deal, they will keep getting knocked back in the queue as other hotels offer better deals. It’s effectively an auction on awesome deals
3. The fact the deals are awesome is what gets people to open that email
4. The deals are all set-up so that you need to buy that day (and in some cases a limited amount available), which creates urgency. But you don’t have to select your date when you buy the coupon. This lets you make impulsive hotel purchases. You don’t need to check with your spouse. You don’t need to plan for someone to take the kids. You just see a great deal for a San Francisco hotel and say, “Wow. I would love to go to SF in the next year. This is a great excuse. I’ll buy this now and then figure out a way to plan that trip.”
5. Now you are getting incremental sales – which is what Expedia and the Hotel partners want. You are getting people to buy these coupons who might not have even bought in that city before.
6. Some people won’t use the coupons. In fact many won’t. People will buy them as an option (“$100/night for a four-star in Manhattan! Great. I’ll buy 3 nights and make it a long weekend…”). But then life will get in the way and what seemed like a great idea in January is becoming too hard to plan in September. And besides, flights were more expensive than we though. I guess I’ll write off that $300. Hopefully I will make it up next time.
7. The non-use of coupons (breakage) will allow hotels to offer even better deals (if there is 50% breakage, than a discount with is actually no discount at all!). And as the deals get better the cycle repeats itself

Unfortunately that world never happened so we will never know. But hopefully the story helps you the next time you are trying to create a new product. Remember the power of scarcity.

This was the original introduction on the homepage of the blog. Today I updated it with a new homepage, but I wanted to keep this short introduction on the blog so I could link to it as necessary. 

Three things I believe

1. If you think marketing is hard, you are likely ignorant (not stupid)
2. The most fundamental job of a CMO is to understand Customer Lifetime Value, but new customers are far more important than existing customers
3. Brand marketing is very important but measuring it is mostly a waste of time

I will provide more background on each of those beliefs in the future. When I do I will link to them from this post.

I was in Groupon’s office in December 2010 when they received an offer from Google to buy the company for $5 Billion. They ended up turning down the offer and taking the company pubic at an even higher valuation, only to have it crash later when it became clear the company couldn’t sustain itself.

The top complain I’ve heard on why Groupon ‘failed’ was that its core product of 50% off with 50% margins did not work for merchants, and as soon as they made it work for merchants (by making the discounts less ‘real’) it stopped being compelling for consumers.

While I won’t disagree with that, I think the reason they failed was subtly different. I believe they failed because they forgot about the power of scarcity.

To understand that power we need to go back to before the first dot.com boom. Back to when Hotels.com was still 1-800-HOTELS.

Here is how 1-800-HOTELS got started:

They would launch in a market (a city). They would call all the hotels in that city and say: “We would love to put you up as an option when people call 1-800-HOTELS. Here is how it will work: You need to offer the consumer 50% off the rate they would get if they called you directly, and we will take 50% margin.”

That’s a 75% discount! What hotel would sign-up for that?

Turns out the smart ones would. A hotel is very high fixed cost and very low marginal cost. So if a hotel has a single empty room, they can make more money by filling it at a 90% discount than if they leave it empty. If they filled all their rooms this way they would be in trouble, but if they haven’t managed to fill rooms, then filling one at a huge discount makes sense.

But wouldn’t the smart hotel fill all their rooms? Nope. If you are a smart hotel and all your rooms are consistently selling out you have your prices wrong. You should be raising your prices and ending up with some vacancies (and have rooms available at the last minute for people who are price insensitive).

So most hotels will have empty rooms (at some price). If they could fill them with 1-800-HOTELS they should.

The problem is most hoteliers haven’t internalized the last few paragraphs. They aren’t quantitative data-driven marketing experts. They are operators who are much better than I am at actually running hotels. They haven’t put in the time to fully grasp the marginal economics. And they definitely didn’t get it 20+ years ago when someone from 1-800-HOTELS gave them a call asking them to join the program.

So why did 1-800-HOTELS work?

Because they didn’t need all the hotels to sign-up. They didn’t need most of the hotels to sign-up. They likely needed about 10 hotels per city to make their model work.

Here’s how it would work from the consumer side:

You call 1-800-HOTELS. You speak to an operator and tell her which city you are looking for and maybe what type of hotel (4-star for example). The agent pulls up her list. She says, “Yes. It looks like I do have a 4-star hotel available. In fact I have it at 50% off. Would you like me to book it for you?”

You may ask for more options, but would it matter if she only had one? 50% off is a pretty great deal. Maybe if you were a business traveler and someone else was picking up the bill you might demand a specific location, but for the rest of us it’s a pretty good solution. Chances are you don’t know where you should stay in the city anyway most of the time.

So 1-800-HOTELS doesn’t need all the hotels. They need one or two in each ‘category’ (in this case I’ll bet a ‘category’ is a general price point and location). So about 10 per city.

They don’t need all the hotels to ‘get it’. They need about 10 of them.

That is the power of scarcity.

Note that power doesn’t exist in classified sites. Hotels.com today needs as much inventory as they can get. It’s been shown that more inventory is the number one driver of both short-term conversion rate and long term success for classified-type businesses. Craigslist doesn’t have a very good product (as many entrepreneurs tell themselves as they try and create CL-killers), but they have all the inventory – and you can’t beat inventory.

Unless you can build a model that doesn’t need inventory. Something that relies on scarcity.

Priceline did it.

1-800-HOTELS continued to grow their inventory over time and eventually got bought by Expedia. Now Expedia had all the inventory. How was a new entrant supposed to compete.

Priceline changed the game – basically by re-inventing 1-800-HOTELS for the internet age. On Priceline you put in a ‘bid’ for a hotel, and only after you commit to staying at a 4-start hotel with a pool in Boston for $83.50 do they tell you if (1) You bid was accepted, (2) Where you are staying.

A lot has been said about the auction system for Priceline (and how it differs from the set-price of Hotwire), but to me the big winner here was that they created scarcity: Expedia needed all the inventory, and Priceline needed about 10 hotels per city (willing to deep discount).

Once you recognize this concept you see it everywhere. Google has effectively unlimited ad space, but they only have one top spot for any given keyword. By creating that scarcity they let the market bid up the value for that spot. If Google had just created a bunch of ad units and then sold them at fixed prices they would not be the giant they are today.

Which brings us back to Groupon.

When Groupon launched they offered one single deal a day per city to their subscribers. They had to start out in hard-core sales mode negotiating those deals with skeptical merchants. But they had the power of scarcity on their side. They only needed one deal a day to make the model work (and there are a LOT of merchants in any given city).

In fact the model worked so well that they soon had waiting lists going out 6-months or more in many cities. At the same time consumers LOVED the deals (who wouldn’t – they were great deals at this point) and were willing to get more than one deal a day. This wasn’t lost on other entrepreneurs who started competitors to try and pick off demand on both sides that Groupon couldn’t fill.

This is where Groupon took a wrong turn.

They saw these competitors popping up and said, “We already have users that would be willing to get more deals. And we have a six-month waitlist for merchants, why don’t we start giving out two deals a day?”

In fact there is no real limit to how many deals Groupon could give out to users. What started with 5 deals a week turned into 7. Then into 14. Then 21. Now it’s off the charts. I just checked out their Seattle page where there are 16 DAILY deals (that’s 112 if it repeats all week which I expect it will).

What does this reduced scarcity do?

It allows the merchants to negotiate for ‘less good deals’. Groupon’s margin decreases, and the quality of the deal to the consumer decreases. Instead of deals like “50% off one of the best restaurants in the city any time”, you now see deals like this:

29% off River Rafting, only available June 7, 14, 15, 21, 28, 29 or July 12 (Even better: They have the same discount on their website: “ONLY $99 (Normally $139) with code ‘RAFTNOW’ at checkout!)

Or

$35 of $60 worth of food at Ipaneme Grill (where the price for their core offering is $50 all you can eat meat, so in practice you are either paying $35 for $50, or more likely $75 for $100 for two people)

Basically Groupon went from have a deal every day that was so fantastic it made sense to stop and read it every day and buy it if you were at all interested, to a place that distributes standard coupons. These coupons have been around forever. Some of them are good, but most aren’t, and the time and trouble it takes to figure out if it is worth it usually isn’t worth it.

But what if they had done it differently?

What if, instead of going from one deal a day to 16 deals a day, they had stayed at one deal?

All of a sudden the arguments about whether or not Groupon was good for merchants would become moot. Only 365 merchants a year would be able to offer deals. If you offered a ‘standard deal’ (50% off at the right price point with 50% margin to Groupon) you go the back of the queue. Your deal may go live in a year. If you want to do something faster than you could offer a better deal to skip the queue. Groupon could develop tools to determine in advance how good a deal was (not just discounts – you could imagine a good deal at a top in-demand restaurant is more valuable than a great deal as an average place). Another component to the deal is how many vouchers you would allow to be sold (more is better).

Basically Groupon would need to develop a ‘quality score’ for each deal to rank them. And then let the highest quality deals be shown first (the second best can wait in line, the third best sit there only to be used if they have a gap in inventory for some reason).

Now this method may mean that at first Groupon does not sell as many deals as their ‘lots of deals’ model. Initially when they moved to 14 deals a week, they likely saw an uptick in sales. They even created a special team whose job it was to determine what the ‘lead deal’ should be for each used based on their demographics and purchase history. You have to believe that if, instead of a Nail Salon deal only, they had a Nail Salon AND a restaurant deal they would get more sales.

The problem is, as soon as you go down this path you start messing with the very thing that made the business successful: Scarcity.

My idea of staying at one deal per city per day may be too extreme. Maybe the right answer is to split the city into east and west side, or split the customer base into women and men (or ‘feminine deals’ and ‘masculine deals’). Groupon should have been able to make some smart judgments at this point – if the wait list for a ‘good deal’ was 6 months then maybe start 2 deals/day. If the it was only 1 month than maybe pull back on the number of deals. They could test the impact on inbound inquiries and deal quality scores based on the length of the wait list.

Instead what was done (I believe) is they tested the revenue impact of going to 2 deals (which was significantly positive the first day it was done). Then they tried 3 and that worked too. Then they started extrapolating how many they could do and they started hiring sales people to fill the now enormous queue. All of a sudden instead of being order takers of a very valuable scarce product they were salesman trying to convince merchants to let them distribute coupons.

It was the beginning of the end.

The Message:

Scarcity is a very very powerful thing. You want to do everything in your power to create it when you are building a business. And once you have it, you want to hold onto it and monetize it the best you can. Do not be tempted to take the short term benefit of selling more if it means giving up on that exclusivity.

There are lots of examples of companies using scarcity (or artificial scarcity) to their advantage. If you can think of some, feel free to comment below.

First: Apologies. When I started this blog in January I planned on a post every week. That lasted through to March. Then life got in the way (as it often does) and this blog fell off the priority list. Part of the problem was with my ambition on the type of content I wanted to share: The ‘Chapters’ for the book are all pretty meaty and rather than put up something half-thought through I just haven’t put up anything at all.

Second: My plan is to get back to the once a week blog post. I’ve come to accept that that will mean many of the posts will not be book chapters. Instead I will put out some form of content that will at least be helpful. I often find myself putting something about marketing or business in writing to friends or colleagues. My new plan is to just share that correspondence publicly here in weeks when I don’t have a new chapter to share.

Third: In the three months that I have slacked off in content generation I have managed to significantly grow my Twitter presence. I’ve grown my following from ~150 to over 4000 today. Most of my followers are marketing professionals themselves. I share a little of how I did this on my updated Twitter Follow-back page.

Finally: Here is my short post this week based on a conversation with the CEO/founder of ZendyBeauty.

ZendyBeauty is a start-up building “Priceline for Elective Surgery”. Basically by giving up exact choice on your provider and specific time of day of your appointment they will get you dramatic discounts on things like Liposuction or Botox. They have build a solid business and now they want to scale and they believe they need marketing help to do it.

These guys did it right. They started by building a product and testing it to make sure customer demand existed (in their case on both sides – the patients and the doctors). They refined their model until they got something that they know worked. They kept their costs low while this was happening, but now they are readying the ‘spend money to make money’. The problem is the skill set they have in house is all product and no demand generation.

This issue is common for start-ups that get to this stage. Rarely do you want a marketer on your team early on (unless they have other skill sets). But then you desperately need one and you don’t know how to find the right person.

The next problem you have is that, since it’s your first marketing person you need someone who can do everything. But you already have the core leadership team and can’t afford to bring in someone very senior at this stage (since you haven’t done any marketing to scale your business yet). It’s a bit of a chicken and an egg problem.

Here was my proposed solution:

Most of the time when you are looking to hire someone you have a total cash comp in mind that you are willing to pay. You also want the world (I love reading job descriptions where they are asking for the skill set of an SVP and for job titles like Specialist or Manager with ‘competitive compensation; of up to $60K). For any given compensation level you will have to choose what you want more of and what you are willing to accept less of (if you cant choose you can always hope to get lucky low-balling someone or you can choose to pay more).

Let’s assume, since you are a start-up, that you can’t pay more. Now you need to decide where you are willing to compromise. I like to think of any potential hire as fitting into one of three stereotypes:

1. The IQ-Jock
2. The All Round Player
3. The Specialist

The IQ-Jock is someone who has limited to zero experience in the role you are looking to hire for. But they have potential. They are really smart. Maybe they can learn to do the job?

The opposite of the IQ-Jock is the All Round Player. This is someone with experience doing everything you need. They know how to do social media marketing, and they can build your Google Adwords account, and they know the basics of content marketing. Oh and they’ve run email programs and done a little design and brand work. And PR. And television buying and… Basically they are a dream. The problem is that if they can really do all that stuff well they should be a CMO making a lot more than your start-up can afford. In practice they have touched on all those areas but they aren’t super skilled in any of them. It’s just not possible. There is too much to know.

The third type of hire is The Specialist. The Specialist has had a focused career in marketing. They have only really done Google AdWords or they have only done Social Media or they have only done Content Marketing. If you are lucky though they have been at an organization where they were sitting next to someone who did some other type of marketing. Since they have been in the space for some period of time they hopefully know enough to be dangerous in their non-specialty areas. But they definitely don’t meet half the criteria on they job description you wrote.

Most companies for most roles end up hiring the All Round Player. The ARP is the only one who actually checks the boxes on your laundry list of a job description. The Specialist can do some of it and the IQ-Jock really can’t prove she can do any of it.

Let me make a case of our two under-appreciated potential hires:

I like hiring IQ-Jocks a lot. You get less experience, but instead you get a lot more intelligence. The draw-back is you need to invest in training them and getting them up to speed. The advantage is once they are up to speed they should be able to figure a lot of things out on their own and take your training and run with it. The problem with IQ Jocks in this specific situation is you have no one else in marketing to teach them the basics. It could still work (you get them signed up with online training programs and count on their diligence to learn it all on the job), but it’s super risky. And your start-up has enough risk already. That said, if a founder has a strong marketing background then IQ-jocks can be a great “second marketing person”

I think in this case I would strongly argue for The Specialist. First, figure out what type of marketing you need the most. Then hire someone who is a specialist in that area. But here is the pitch: You hire them to blow away the area you need most, but they get the opportunity to do all those other marketing things they have seen but haven’t had a chance to do. It’s a great deal for them to develop their career and prove themselves. And because it’s a great deal for them you can get them at a discount. You should be able to pay them parity to what they are currently earning doing one activity and get them to deliver across your whole portfolio. And they have proven themselves to be an expert in a  specific area, so you know there is at least a basic level of competence.

Disagree? Other ideas on how you can hire for the first marketing role? I would love your comments below.

There are 24 Oscar categories. Trying to get them all right is very hard. Especially this year.

I’m so confident it can’t be done I’m willing to pay $12,000 to whoever can do it.

All you need to do is send me your complete predictions for all of the categories (Tweet them to me: @ednever, email them to me: Edward at MarketingIsEasy dot com, or put them in the comments below). Make sure you do it in a way that I can reach out to you afterwards if I am wrong and someone actually pulls it off.

For extra fun, if no one gets them all right, I will still send $10 to whoever got the most right. Heck. If the winner gets 20 or more right I will up that to $100.

You have nothing to lose (I have a LOT to lose…)

Send me your predictions and let’s make it an exciting Oscars!

Questions:

Is this for real?

Yes. I have the money. You will be paid if you get them all right. In the absurd possibility that more than one person gets them all right, you will have to share the $12,000. I will only honor one entry per person (i.e., if you submit more than one and I catch you, you are out of luck)

Why are you doing this?

First, because I don’t think it can be done. If you have a 50/50 chance of getting a category right, then there is about a 1/16 million possibility to get them all right. If I really get 16 million proposals my bigger problem will be going through them more than paying the $12,000!

Second, because I think it might be fun.

Third, purely self-promotional. Maybe it drives more people to check out this blog (is it why you are reading this?)

How will I get paid?

We will figure it out. PayPal or something. I could always just write you a check and send it in the mail.

Is this some sort of company promotion?

No. Just me.

What about terms and conditions and stuff?

Just that I will only pay out if someone gets them all right. And I will only pay out $12,000 maximum. And you need to submit before the start of the telecast (obviously). That’s it. I don’t think we need a lawyer, since the payout comes until the category of a ‘gift’ ($12,000 is the maximum you can gift someone). No need to overly complicate this thing.

More Questions?

Just leave a comment below or reach out to me on Twitter or Email.