Until a week ago I was Vice President of Marketing for VeriSign's Trust Services (SSL) business, recently acquired by Symantec. I was with the company for almost seven years and built my department from nothing to the point where there were twenty people under me. I am a big believer in investing in people to grow them and improve the value they have for the company.
To help the marketing staff continue to learn and improve, one thing I did was to create BOOK GANG. BOOK GANG stands for Business Optimization Oriented Knowledge Gatherers Acquiring Necessary Grokitude, and it was a voluntary book club consisting of VeriSign marketing employees who wanted to increase their marketing and business skill set. Each month we'd choose a book and read it, and then BOOK GANG would assemble for lunch on a scheduled day to discuss the book and how it applied to our own business. At the end of the meeting we would choose the next month's book.
I covered the books and the lunch from my budget. Everyone else's part of the deal was to read the book (I read them also). Any time prior to purchasing the books a participant could drop out for that month without penalty, but if you don't get two of the books read, you're kicked out of BOOK GANG.
I liked it a lot as a program. It was a very inexpensive way to improve our employee assets and to give us a common vocabulary and framework that we could use to think about relevent marketing programs for our own business. It showed the employees that the company wanted them to succeed. It gave them something to belong to and deepened relationships between people who otherwise wouldn't work with each other that much. It was fun. Wherever I land in my career, I'll continue to invest in programs of this sort.
BOOK GANG continues without me. I won't be a participant moving forward, but I'll try to pull some of the old BOOK GANG books off my shelf and write a bit about them.
Saturday, March 26, 2011
Sunday, March 20, 2011
The five qualities of successful experimental marketing programs
In the high technology space marketers often find themselves attempting to develop new marketing and sales models. Maybe you're going after a new segment or offering a new product. Oftentimes the mix of marketing and sales activities you use for your established products and customer bases are not successful with these new initiatives, even if the product itself is solid and the customer need real.
Under these circumstances marketing and sales leadership find themselves in the mode of discovering a business model rather than executing a business model. In other words, the point of marketing and sales activities is not actually to make money but rather to determine the methods that will enable the company to build up to a successful revenue stream.
This distinction is important and in my experience usually lost on those responsible for marketing and sales strategy. Therefore you see behaviors like forcibly growing revenue at negative profit by scaling up programs that are too inefficient to be sustainable ("We're losing money on every unit sold, but we'll make it up in volume") or plugging away at some minor, one-off program that at best can hope to yield a few hundred thousand dollars ("There are only fifteen target customers in the world, but damn it, we'll get 'em all"). These are bad decisions in all but the most extreme circumstances, but they happen routinely when an organization becomes completely focused on hitting a revenue target (executing a business model) as opposed to building the knowledge base that will later allow you to grow and profit at the same time (discovering a business model).
When I'm in charge of the marketing for a new product initiative, I always insist on understanding whether we're executing a proven business model or seeking a new business model. And even in the case of existing, successful businesses, often companies are trying to expand into parallel markets or improve efficiency or simply eat their own children before competitors do. In these cases a company may actually run both activities simultaneously, sometimes even on the same customer base.
When marketing programs are in place to seek a business model rather than execute one, then I have a handy list of the five key qualities to which an activity or campaign must adhere. Violate any of these rules and you're getting confused about the distinction between seeking and executing, to your own detriment.
Successful experimental marketing and sales campaigns and activities must be,
Testable. When we're seeking a business model, that means we're in a scientific mode. We have hypotheses about how our activities may affect customer behavior, ultimately resulting in sales. We spend our budget, skill, and manpower to test these hypotheses, and based on the measured results of these tests, we can adopt and implement ideas (a home run), further explore or refine where potential appears to exist (a base hit), or abandon them completely (strike out). Without the testing component, there is no progress. We don't know what we can scale up and what we need to modify and what we simply throw away.
Note that not all tests result in metrics or numbers. Often that's what we're looking for (e.g. leads generated or incremental sales booked), but sometimes the test is softer. Was there a lot of interest at the trade show booth? How much PR pickup did we get? Does the partner community approve of the idea? These test results are also very important, even though they aren't conducive to an ROI calculation.
Repeatable at scale. The point behind testing is that when you find the results that work, you can go out and do them again, and ideally you can do them much bigger than you did the first time. The classic example is a direct marketing program (let's say direct mail to a specific target list) in which we measure the ROI of the program. If it's positive, we can then run everything at ten or 100 times the scale of the original test. Upside is large and downside is small.
Activities that aren't repeatable at scale are not model-seeking activities. A one-off, unique opportunity that will never come up again in your lifetime is not repeatable. Even if it's gloriously successful, there's nothing you can do with that. Now, a marketer may still decide to take a flyer on such an event, if the price is right and it seems likely to help the business. But under those circumstances that is a business model execution decision, not a business model seeking decision. You're running the program for the direct benefit in itself, not for knowledge that you will apply in a scaled-up fashion.
Affordable. One fact of life is that we have limited resources. Budget, time, attention, development roadmap, number of times you can send offers to your installed base without burning them out - all these things are examples of finite resources that can run out.
Experimental programs consume these resources, just as model-driving programs do. The more resources you spend on your experimental program, the less you have to get to your critical business number. Therefore when running experimental programs, it's important to keep a tight grip on running affordable programs.
If we use the above direct mail example, test cells can often be very small compared to the dialed-in programs that you run at scale. If your average test sell is just a few percentage points the size of a scaled-up program, then you can afford to try out some reasonable hypotheses. If they don't turn out, you haven't lost much, but if they do work, then you can suddenly multiply them thirtyfold and enjoy a big win.
Offering speed to results. If we're here to learn, then speed to results is critical. I want a program where I can have a sense for how it turned out in a few days and a fully valid result in a month. That's important because the experimental programs themselves (being small in scale, likely not to work out, and never fully optimized) even under the best of circumstances do not constitute business success. We have to take those results and implement them before we get the financial and market rewards we require to call our businesses successful. Add in the fact that discovering the right sales and marketing model often requires multiple - and sometimes many - iterations, and you have an environment where speed is key.
Not absurd. Note that I didn't say proven or certain or unable to fail. Note that I didn't even say likely. Often these are the standards business hold all marketing and sales activities up to before giving them the green light. If you do that, then you'll create an environment where you never can truly experiment. Instead, we need a lower standard than that.
Now, I said not absurd because we're not here to do dumb stuff either. Remember that earlier discussion of limited resources? We certainly can't be wasting them, not even in our experimental programs. Therefore each experimental program has to be based on a reasonable hypothesis, one that seems to have a very real chance of success. There's nothing wrong with some of your ideas not panning out. Otherwise you're probably not being aggressive enough in your experimentation and therefore missing out on some of your potential. But at the same time, make sure that everything you try is offering a genuine, legitimate contribution to the base of knowledge you have for your market and its responses to your products. Make sure you only try things that might work.
Apply all five of these criteria rigorously to all experimental marketing and sales activities you undertake in your organization, and you'll be a step ahead on discovering those new opportunities and markets and offerings than you would be any other way.
Under these circumstances marketing and sales leadership find themselves in the mode of discovering a business model rather than executing a business model. In other words, the point of marketing and sales activities is not actually to make money but rather to determine the methods that will enable the company to build up to a successful revenue stream.
This distinction is important and in my experience usually lost on those responsible for marketing and sales strategy. Therefore you see behaviors like forcibly growing revenue at negative profit by scaling up programs that are too inefficient to be sustainable ("We're losing money on every unit sold, but we'll make it up in volume") or plugging away at some minor, one-off program that at best can hope to yield a few hundred thousand dollars ("There are only fifteen target customers in the world, but damn it, we'll get 'em all"). These are bad decisions in all but the most extreme circumstances, but they happen routinely when an organization becomes completely focused on hitting a revenue target (executing a business model) as opposed to building the knowledge base that will later allow you to grow and profit at the same time (discovering a business model).
When I'm in charge of the marketing for a new product initiative, I always insist on understanding whether we're executing a proven business model or seeking a new business model. And even in the case of existing, successful businesses, often companies are trying to expand into parallel markets or improve efficiency or simply eat their own children before competitors do. In these cases a company may actually run both activities simultaneously, sometimes even on the same customer base.
When marketing programs are in place to seek a business model rather than execute one, then I have a handy list of the five key qualities to which an activity or campaign must adhere. Violate any of these rules and you're getting confused about the distinction between seeking and executing, to your own detriment.
Successful experimental marketing and sales campaigns and activities must be,
- Testable
- Repeatable at scale
- Affordable
- Offering speed to results
- Not absurd
Testable. When we're seeking a business model, that means we're in a scientific mode. We have hypotheses about how our activities may affect customer behavior, ultimately resulting in sales. We spend our budget, skill, and manpower to test these hypotheses, and based on the measured results of these tests, we can adopt and implement ideas (a home run), further explore or refine where potential appears to exist (a base hit), or abandon them completely (strike out). Without the testing component, there is no progress. We don't know what we can scale up and what we need to modify and what we simply throw away.
Note that not all tests result in metrics or numbers. Often that's what we're looking for (e.g. leads generated or incremental sales booked), but sometimes the test is softer. Was there a lot of interest at the trade show booth? How much PR pickup did we get? Does the partner community approve of the idea? These test results are also very important, even though they aren't conducive to an ROI calculation.
Repeatable at scale. The point behind testing is that when you find the results that work, you can go out and do them again, and ideally you can do them much bigger than you did the first time. The classic example is a direct marketing program (let's say direct mail to a specific target list) in which we measure the ROI of the program. If it's positive, we can then run everything at ten or 100 times the scale of the original test. Upside is large and downside is small.
Activities that aren't repeatable at scale are not model-seeking activities. A one-off, unique opportunity that will never come up again in your lifetime is not repeatable. Even if it's gloriously successful, there's nothing you can do with that. Now, a marketer may still decide to take a flyer on such an event, if the price is right and it seems likely to help the business. But under those circumstances that is a business model execution decision, not a business model seeking decision. You're running the program for the direct benefit in itself, not for knowledge that you will apply in a scaled-up fashion.
Affordable. One fact of life is that we have limited resources. Budget, time, attention, development roadmap, number of times you can send offers to your installed base without burning them out - all these things are examples of finite resources that can run out.
Experimental programs consume these resources, just as model-driving programs do. The more resources you spend on your experimental program, the less you have to get to your critical business number. Therefore when running experimental programs, it's important to keep a tight grip on running affordable programs.
If we use the above direct mail example, test cells can often be very small compared to the dialed-in programs that you run at scale. If your average test sell is just a few percentage points the size of a scaled-up program, then you can afford to try out some reasonable hypotheses. If they don't turn out, you haven't lost much, but if they do work, then you can suddenly multiply them thirtyfold and enjoy a big win.
Offering speed to results. If we're here to learn, then speed to results is critical. I want a program where I can have a sense for how it turned out in a few days and a fully valid result in a month. That's important because the experimental programs themselves (being small in scale, likely not to work out, and never fully optimized) even under the best of circumstances do not constitute business success. We have to take those results and implement them before we get the financial and market rewards we require to call our businesses successful. Add in the fact that discovering the right sales and marketing model often requires multiple - and sometimes many - iterations, and you have an environment where speed is key.
Not absurd. Note that I didn't say proven or certain or unable to fail. Note that I didn't even say likely. Often these are the standards business hold all marketing and sales activities up to before giving them the green light. If you do that, then you'll create an environment where you never can truly experiment. Instead, we need a lower standard than that.
Now, I said not absurd because we're not here to do dumb stuff either. Remember that earlier discussion of limited resources? We certainly can't be wasting them, not even in our experimental programs. Therefore each experimental program has to be based on a reasonable hypothesis, one that seems to have a very real chance of success. There's nothing wrong with some of your ideas not panning out. Otherwise you're probably not being aggressive enough in your experimentation and therefore missing out on some of your potential. But at the same time, make sure that everything you try is offering a genuine, legitimate contribution to the base of knowledge you have for your market and its responses to your products. Make sure you only try things that might work.
Apply all five of these criteria rigorously to all experimental marketing and sales activities you undertake in your organization, and you'll be a step ahead on discovering those new opportunities and markets and offerings than you would be any other way.
Friday, March 4, 2011
Do you need more baskets or do you need more fruit?
I have found that a good analogy goes a long way toward explaining a phenomenon or principle that is complex or dependent on a great deal of specialized knowledge. (More on that topic later, I promise.) Today I'd like to introduce you to the baskets vs. fruit metaphor.
I invented this metaphor to facilitate discussion around how to set a marketing mix between lead generation and true demand generation (or you can call it awareness or preference building or even brand building if you prefer). It's the fruit and baskets metaphor.
Imagine a small village in pre-industrial society. This village is situated on the edge of a medium-sized wood. In the wood can be found fruit trees. The members of the village have learned that they can go into the wood and hunt around, and with sufficient effort they will find trees bearing fruit. They can pluck the fruit and bring it back home, and with enough effort the entire village can eat this way.
Because it's a dense wood and fruit trees are infrequent, it takes a lot of work to find one, and leaving the wood and returning to the exact same tree later is nearly impossible. Furthermore, it can be a considerable trek through the wood to any given tree, meaning that the time required to go back and forth can hack out a decent piece of a given forager's day.
Therefore, someone in the village stumbles on the idea of baskets. The villagers weave baskets and send them out with the foragers. When foragers discover a fruit tree, each can harvest and carry back an entire basketful rather than what can be carried just in a pair of hands. The result is instant and meaningful. Each forager is coming home with more fruit than before. Efficiency is up, and the village is prosperous.
What do the savvy villagers do? Weave more baskets, of course. As they create and send out more baskets, the amount of fruit returning to the village increases. Life is good.
Unfortunately as the villagers continue to produce and release an ever increasing number of baskets, a strange thing starts to happen. Baskets start coming back less than entirely full. Soon the average baskets is only 80% full when the forager returns from the wood.
How do the villagers address this problem? More baskets! They produce a bunch of additional baskets and send them out into the wood, but now the baskets are coming back 50% full and the villagers are still behind on their production goals. I'm sure you know what the villagers do next.
That's right. They produce a whole boatload of new baskets and send them into the wood. But now the baskets are coming back only 20% full and the villagers continue to fall short of their fruit production quota.
I hope the metaphor is obvious. The village is your company, and the wood is your market. Fruit is revenue (or unit volume, or customers, it doesn't really matter to the metaphor). Foragers are sales professionals, and baskets are lead-generating marketing activities. In the beginning the company has sales professionals who are getting sales the hard way, one at a time, as so many companies do in the beginning. The company discovers lead gen, and originally the results are fantastic. Sales are up, sales efficiency is up, and life is good. We're all gonna be rich.
However, as the company continues to scale, it inexorably finds that lead generation efficiency declines. Each dollar spent earns less than the previous dollar. Marginal contribution of marketing spend drops, and ROI declines until it reaches or even drops below the breakeven point. Business plans never seem to account for this phenomenon; managers seem to think they can scale anything to infinity and never hit a wall. Therefore the company is suddenly behind target as sales and marketing efficiency has inexplicably slipped from where it was this time last year.
So what do they do? More lead gen! I've seen this response more times than I can count. Sure, we're losing money on every letter we send, but at least we can get to our revenue goal. And you can buy some sales that way, but of course the lead generation efficiency just continues to drop and it gets more and more costly to artifically drive your growth.
The problem the villagers face is not that anything is wrong with their baskets, nor that they have too few of them. The villagers' problem is that they don't have enough fruit. They have gotten to the point where they're havesting the fruit as fast as the wood produces it. If the village is to continue its growth, its inhabitants need more and better sources of food, not more and better ways of transporting food back to the village. In the real world, the company is maximized on its demand realization initiative, and to continue to grow it needs to increase the amount of demand the market has for its goods and services.
So if weaving more baskets won't solve the problem, do the villagers just throw in the towel and starve? Of course not. There are lots of things they can do to produce more food. The village can:
I invented this metaphor to facilitate discussion around how to set a marketing mix between lead generation and true demand generation (or you can call it awareness or preference building or even brand building if you prefer). It's the fruit and baskets metaphor.
Imagine a small village in pre-industrial society. This village is situated on the edge of a medium-sized wood. In the wood can be found fruit trees. The members of the village have learned that they can go into the wood and hunt around, and with sufficient effort they will find trees bearing fruit. They can pluck the fruit and bring it back home, and with enough effort the entire village can eat this way.
Because it's a dense wood and fruit trees are infrequent, it takes a lot of work to find one, and leaving the wood and returning to the exact same tree later is nearly impossible. Furthermore, it can be a considerable trek through the wood to any given tree, meaning that the time required to go back and forth can hack out a decent piece of a given forager's day.
Therefore, someone in the village stumbles on the idea of baskets. The villagers weave baskets and send them out with the foragers. When foragers discover a fruit tree, each can harvest and carry back an entire basketful rather than what can be carried just in a pair of hands. The result is instant and meaningful. Each forager is coming home with more fruit than before. Efficiency is up, and the village is prosperous.
What do the savvy villagers do? Weave more baskets, of course. As they create and send out more baskets, the amount of fruit returning to the village increases. Life is good.
Unfortunately as the villagers continue to produce and release an ever increasing number of baskets, a strange thing starts to happen. Baskets start coming back less than entirely full. Soon the average baskets is only 80% full when the forager returns from the wood.
How do the villagers address this problem? More baskets! They produce a bunch of additional baskets and send them out into the wood, but now the baskets are coming back 50% full and the villagers are still behind on their production goals. I'm sure you know what the villagers do next.
That's right. They produce a whole boatload of new baskets and send them into the wood. But now the baskets are coming back only 20% full and the villagers continue to fall short of their fruit production quota.
I hope the metaphor is obvious. The village is your company, and the wood is your market. Fruit is revenue (or unit volume, or customers, it doesn't really matter to the metaphor). Foragers are sales professionals, and baskets are lead-generating marketing activities. In the beginning the company has sales professionals who are getting sales the hard way, one at a time, as so many companies do in the beginning. The company discovers lead gen, and originally the results are fantastic. Sales are up, sales efficiency is up, and life is good. We're all gonna be rich.
However, as the company continues to scale, it inexorably finds that lead generation efficiency declines. Each dollar spent earns less than the previous dollar. Marginal contribution of marketing spend drops, and ROI declines until it reaches or even drops below the breakeven point. Business plans never seem to account for this phenomenon; managers seem to think they can scale anything to infinity and never hit a wall. Therefore the company is suddenly behind target as sales and marketing efficiency has inexplicably slipped from where it was this time last year.
So what do they do? More lead gen! I've seen this response more times than I can count. Sure, we're losing money on every letter we send, but at least we can get to our revenue goal. And you can buy some sales that way, but of course the lead generation efficiency just continues to drop and it gets more and more costly to artifically drive your growth.
The problem the villagers face is not that anything is wrong with their baskets, nor that they have too few of them. The villagers' problem is that they don't have enough fruit. They have gotten to the point where they're havesting the fruit as fast as the wood produces it. If the village is to continue its growth, its inhabitants need more and better sources of food, not more and better ways of transporting food back to the village. In the real world, the company is maximized on its demand realization initiative, and to continue to grow it needs to increase the amount of demand the market has for its goods and services.
So if weaving more baskets won't solve the problem, do the villagers just throw in the towel and starve? Of course not. There are lots of things they can do to produce more food. The village can:
- Visit another wood. Maybe there's another wood within walking distance, and maybe that wood has fruit in it. Surely it's not as convenient as the wood we're used to, but it's better than starving. Translation: Expand into new markets where analagous target buyers will need your product. Maybe that's a new geography or a new industry vertical or a different size of business. Surely it will be more difficult than the market you already know, but it beats missing your financial targets.
- Start digging for tubers. Maybe there are other things to eat than fruit in this wood. Maybe the foragers can look for that also while they're out. They might need new tools and training, but you can divert energy from making baskets to provide those. Translation: What else can you sell to these same people who are buying from you today? You can still increase revenue if you increase wallet share rather than increasing the number of actual logos that buy from you.
- Plant fruit trees. If the village looks far enough into the future, it can plant fruit trees so that in a few years it will be able to add them to its yield. The villagers need to plan in advance, of course. That requires forward-thinking management that isn't always there. Translation: Invest in developing your market well in advance of the time your growth starts to flag. So often I see businesses fail in this way. They're growing fast and making lots of money, and clearly they must be invincible. Therefore, instead of pouring profit back in and building for the future, they suck it out as fast as they conceivably can. Maybe the reasoning is that it'll be the next guy's problem to solve, not yours. But if you plan on being around for the long haul, make sure you don't do something today that will stab you in the back five years from now.
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