Category Archives: Startups

The Sales/Marketing Expense Ratio

Question:  how much does a $15M SaaS company spend on sales and marketing as a percent of ARR?  Answer:  35% (with 45% and 15% as the top and bottom quartiles).

Charts like this, from OpenView’s 2021 Financial & Operating Benchmarks survey, help to answer questions like that all the time.

Good SaaS executives keep these metrics in mind, and you can get them from KeyBanc, RevOps Squared, OpenView, or for bigger/public companies, sites like Meritech Public Comps, Public Comps, or Clouded Judgement.

A great revops or FP&A person will give the answer from multiple sources and explain the differences among them.  Moreover, they’d observe that sales and marketing (S&M) expense really should vary with growth rate, and they’d know that KeyBanc tracks that:

So if that $15M SaaS company is growing at 25%, then median S&M spend is 20% of revenue, whereas if it’s growing at 70%, then median S&M spend bulks up to 46%.

But that’s all SaaS Metrics 101.  Today, I’d like to hop to the 201 level by introducing a simple that metric that can reveal a lot and on which few people focus:  the sales/marketing expense ratio, which just equals sales expense divided by marketing expense.

To introduce the idea — quick, tell me what’s happening at this company:

My take:

  • The company is high relative to the benchmark
  • The company is not making much progress towards the benchmark
  • Sales is getting less efficient while marketing is getting more efficient

This situation is very common.  Sometimes, it’s justified bottom-up — e.g., we’re building a partners function in sales that is only slowly becoming productive and we’ve upgraded both marketing leadership and the martech stack to improve marketing efficiency.

Normally, it’s not.  In fact, normally, there’s no justification whatsoever.  When you ask, you get, “well, that’s just how the budget process worked out, the real focus was on improving S&M and we did.  Next question, please.”

Yes, you did improve S&M, but you put the “S&M” improvement 100% on the back of marketing (in fact, 200%) and with no bottom-up justification for why sales needs to get more expensive while marketing is going to magically become more efficient.  This is a mistake.  The likely result is underfed sellers screaming for pipeline, forming an angry mob with dogs and torches headed to the CMO’s office.

Let me tell you what’s going on when this happens:

  • Your CRO is a better negotiator than your CMO.  They better be.  If they’re not, you have an additional problem.
  • Your CRO has more negotiating leverage than the CMO.  They are negotiating the company number directly with the CEO and indirectly with the board.  This is high-stakes, board-level poker.
  • There’s usually no broken-out benchmark, typically only a combined benchmark, and given the prior two points, the CRO is just fine with that.
  • It’s easy to think that hiring sellers “leads directly” to new ARR than investing in marketing.  Why?  Because in enterprise software the bookings capacity model is typically driven off the number of sellers.  Yes, this is intellectually lazy and only works on the margin, but deep down, it’s what a lot of CEOs and CFOs feel.

So the CMO gets asked to suck it up, the board doesn’t notice the problem, the CFO notices but doesn’t want to rock the boat, and the CEO is just happy to get the plan approved.

Hopefully the CRO has the decency to attend the CMO’s going-away party in the fall.  Because if this process repeats itself for even a few years, that’s how it’s going to end.

So how do we fix this?

1. Shine a light on the problem, by adding the sales/marketing ratio to the in-line metrics presented in the plan.

I prefer to show it this way, which makes it clear we used to spend $2 in sales for every $1 in marketing, but that has crept up to over $3.  Showing the metric gives people the chance to ask the all-important question:  why?

The other way to show this is via “sales composition,” i.e., sales as a percent of sales and marketing:

In this case, you can say that sales has risen from two-thirds to three-quarters of S&M expense, and again ask why.  I think the former presentation is more intuitive, but the advantage of this presentation is that KeyBanc benchmarks it in this form:

2. Shine a light on your inverted funnel model.  Sometimes you can squeeze marketing expense just on the people side, but the real way you usually cut to these targets is by making a series of seemingly innocuous assumptions in your funnel.  Consider:

Saying, we need to take MQL to SQL from 10% to 12%, SQL to SAL up from 65% to 70%, and SAL to close up from 15% to 20% all sounds pretty reasonable.  When you combine these effects, however, you’re saying that you’re going to cut the cost of generating an opportunity by more than a third, from $2700 to $1800.  That should get some attention — without any explanation other than the compound effect of small tweaks, it sounds like an Excel-induced hallucination to me.

3. Get the CRO on your side.  Make them understand that squeezing marketing too hard for purely top-down reasons increases their risk on the plan.  Get them to go to bat for you saying, “we need to ensure we feed the sellers enough pipeline.”  Most boards solve for growth with one eye on the CAC and not the opposite.

4. Get the CFO on your side.  In my experience, the hardest person to convince in these debates is the CEO, not the CFO.  Why?  Because the CEO is the one and only person who must negotiate the plan target with the CRO and that’s always something of a painful process.  So, if you get the CRO and CFO on your side, you will greatly increase your odds of getting the CEO to along with you.  You win the CFO over by emphasizing risk.  Think:  “we’ve (finally) got the CRO signed up for the number, but we’ve squeezed marketing too hard and that’s adding risk to the plan” and then say the magic words, “we don’t want to miss plan — do we, CFO?”  They never do.

In a world where sales has more political power, better negotiating skills, and more negotiating leverage than their marketing colleagues, the somewhat natural state of affairs is for this ratio to slowly increase over time.  The question is:  should it?  Everyone on the e-team needs to take accountability for thinking about that and ensuring the company gets the right, not just the easy, answer.  And the CMO has the unique responsibility of ensuring they do.

Everything I’ve Learned About Recruiting and Interviewing

The other day a founder asked me about interviewing because a candidate had described me as “a great interviewer,” and she wanted to know why. (And for that matter, so did I.)

Emboldened by this seeming endorsement, I dashed off what turned into a lengthy email on interviewing and recruiting, a topic about which I am passionate not because I think I am good it, but because I think I am not.  I find interviewing and recruiting difficult, have made plenty of mistakes over the years, and the consequences of those mistakes are invariably painful.  The wise manager approaches recruiting as a great opportunity to strengthen the organization, but does so with some degree of humility, if not trepidation.

Thoughts on The Recruiting Process
Let’s start by sharing some things I’ve learned over the years on the recruiting process, before we dive specifically into interviewing.

  • Know what you’re looking for.  Most troubles begin here because people fail to ponder and debate what they are actually looking for, so you do the equivalent of walking into Costco without a shopping list.  For example, for a seller, do you require software applications, platform, or data & analytics experience?  What size deals?  To line of business, IT, or both?  For a CFO, do you require a accounting or finance background?  A veteran or an up-and-comer?  A CF-No or a CF-Go style?  You should know the answers to these questions; keep yourself honest by documenting them in a must-have / nice-to-have document.
  • Remember it’s a mutual sales process.  Unless you’re blessed to be at the hottest company in town, always remember that recruiting is a mutual sales process.  That means you need to be selling and filtering at the same time.  Particularly at the end of the process, interviewers should be told whether they should be primarily in “sell mode” or “filter mode.”  As it turns out, the person who said I was a “great interviewer” was a late-stage candidate who saw me in sell mode.  (And, yes, we succeeded with the hire!)  But who knows what they’d have thought of me in filter mode?
  • Follow some methodology or book.  I’m not particularly religious about which one, but I think a common framework helps to ensure completeness and improve communication during the recruiting process.   My private equity friends at ParkerGale, who do a great job of methodology selection, swear by Lou Alder so I’ll plug Hire With Your Head here.  ParkerGale has their own hiring playbook available as well.
  • Use work test samples.  While I’m not big into puzzles with prisoners and lightbulbs, I am a huge believer in having candidates do anything that approximates the work they’ll be doing if they take the job.  Have a product marketing manager give a presentation.  Ask a seller to role-play a sales call.  Have an engineer write pseudo-code to generate the Fibonacci sequence (to see if they understand recursion).  My all-time favorite was giving two FP&A directors the same three-tab spreadsheet with instructions “fix it,” “answer it,” and “model it” to test their attention to detail, problem solving, and modeling abilities.  The two were neck-and-neck on paper and in the interviews, but the exercise revealed a massive difference between them.  (We hired the one whose work stood out and were happy we did.)
  • Check references.  While I suppose the standard process of checking candidate-supplied references is still de rigeur, my favorite reference checks are backchannel and framed not in a binary hire-or-not light, but instead in the light of:  if I were to hire them, what strengths and weaknesses should I expect to see and how should I work with them to get the best results?  This framing tends to produce a better conversation.
  • Consider a try-and-buy.  One way to remove enormous risk from the recruiting process is a try-and-buy:  hire the person as a contractor or consultant, try working together for 3 to 6 months, and if both sides are happy at the end of that period, then convert the candidate to regular employment.  This works for some positions better than others — e.g., fractional CFOs and rent-a-CMOs already exist, whereas fractional CROs and CPOs (product) generally do not.  This works for some situations better than others:  it won’t work when recruiting a veteran CMO out of an existing job, but it can work nicely when considering a between-jobs, up-and-coming VP of Finance for their first CFO role.  Be open, be creative.  I’ve made some great hires this way — and avoided some train wrecks.

Thoughts on the Interview
When it comes specifically to interviewing, here’s what I’ve learned.

  • After chit-chat, ask for a N-minute life story with an emphasis on the why, not the what (i.e., why did you major in X, take first job Y, or move to job Z, as opposed to what you did in each).  For math types, I call this the first derivative of your resume.  I like to time-bound it, typically to 5 or 10 minutes, to see if the candidate has the ability to manage time and summarize accordingly.  I like the first derivative because it provides more information:  I already (largely) know what a PMM or VP of Finance does at a software company.  I’d much prefer to hear why someone chose to work (or stop work) at company X.  Moreover, if I want to understand accomplishments or duties, I can ask that separately, not as part of the life story.
  • After hearing “tough, but fair” for the 100th time, I decided to never ask for philosophies of any type, ever again.  Instead, think about situations that are encountered on the job and ask for relevant stories:  tell me about a time your fired someone, tell me about a time you launched a product, tell me about a time you ran the planning and budgeting process.  The experts call this behavioral interviewing, and it works.
  • Drill, baby, drill.   While I first learned this technique as a way to catch liars and exaggerators (who are frequently ensnared by the details), drill-down questions make fantastic follow-ups to behavioral “tell me about a time” questions.  Example:  tell me about a time you ran a budgeting process?  Drill-downs:  what year was it, in what month did you start, what was the rough total expense budget, how did you define the process, how many budget owners were there, how many iterations did you go through, how did you agree on the sales plan, did salesops have their own model, who made the churn plan, did they properly handle multi-year deals, who was the hardest exec to get on target, what were their objections, how did you handle them, when did the board finally approve it, how many iterations did that take, what were the initial objections, what would you do differently?  I’ve literally started down this path and had people say, “uh, I didn’t actually run the process in that job, but I was part of it” — an important distinction.  Whether to catch embellishment or to better understand candidates, drill-down questions work.  It’s more effective to go ten feet deep on one situation than one foot deep across ten.
  • Consider a panel interview.  I’ve become a huge fan of properly conducted panel interviews.  But first, what a panel interview is not:  it’s not randomly throwing 2-3 interviewers into a room with a candidate with no structure or preparation.  That’s called a romp, and it’s usually a negative experience for everyone.  What I’ve seen work is the following:  after a screening process that results in three candidates who meet all must-have criteria, you appoint a lead interviewer to create 5 behavioral questions (based on expected job duties in the first 12 to 18 months), share those questions with the candidate in advance, and then run a 90-minute live interview with a panel of 3-5 members who largely listen and ask follow-up questions only.  You create a scoring rubric, have all interviewers complete it, and then conduct a live discussion to compare the candidates.  This is FIRE.  In theory any of three candidates can do the job, so you’re focused on picking the best one for the company and situation.  The panelists listen intently because they’re not worried about running the interview, the remaining time, or their next question.  All candidates are asked the same questions.  And then you debrief via a live discussion which, as much as I love technology, is far higher bandwidth than any collaboration mechanism.  And you avoid groupthink because the rubric has been completed in advance.  Fire.  I thank ParkerGale for teaching this technique to me; they have a Private Equity Funcast episode on how they approach hiring here.

Why You Should Always Create Sales Opportunities at Zero Dollar Value

Quiz:  Your marketing team generates an MQL.  It’s passed to an SDR, who does basic BANT-style qualification and decides it’s real.  They create a sales opportunity in your pipeline and pass it to a seller.  What number is in the opportunity’s value field at this time?

Four answers I hear frequently:

  • I don’t know.  C’mon Dave, that’s a detail, why would I care about that?  Keep reading.
  • Some semi-random proxy value, say $25K.  Because, well, we’ve always done it that way, and I’m not sure why.
  • Our average sales price (ASP), say $100K.  For extra credit, our segment-specific ASP:  SMB opportunities get valued at $25K and enterprise ones get valued at $100K.
  • Zero dollars.   And that’s the only way I’d ever do it.

What’s my answer?  Zero dollars (and that’s the only way I’d ever do it).  Before I tell you why, let’s remind ourselves why we should care about the answer to this question.

Do you ever look at:

  • Pipeline coverage, as a way to determine your confidence about the future or to give investors confidence in the future?
  • Pipeline conversion rates (on a regular or to-go basis) as a way of measuring pipeline quality or triangulating the forecast?
  • Pipeline generation efficiency (e.g., pipe-to-spend ratio) in order to determine which programs or channels are better than others?

If the answer to any of those question is yes, you need to care about your definition of pipeline.  And while many people think about stage (e.g., should that SDR-created, stage-one opportunity even be considered pipeline?), few people seem to think as much about value.

In a typical funnel [1], by the time you get to stage 3 or 4 of your sales process you may have weeded out half your pipeline.  Now imagine it’s early in a quarter and your pipeline is loaded with stage 2 and stage 3 opportunities, all valued at $100K.  You may have a big air bubble in your pipe.

You think, alas, no worries, Dave, I can handle that in other ways:

  • When we say pipeline around here, we actually mean stage 4+ pipeline, so we just exclude all those opportunities.
  • When we look at stage-weighted pipeline, we weight at 0% all the stage 2 and 3 opportunities, so they’re effectively ignored.

Doing this will bleed a lot of air out of the pipeline, but let’s step back for a minute.  You’re telling me that you’re putting in a $100K placeholder value at opportunity creation time and then systematically ignoring it?  Yes.  Well, tell me again, why are you putting it in the first place?!

The answer to that question is usually:

  • We want to show a big pipeline to get everyone excited.
  • That’s how everybody does it.
  • We want to be able to compare against companies that use placeholder values.

Before challenging those answers, let me object to the air bleeding processes mentioned above:

  • Pipeline should mean pipeline.  If there’s no adjective before the word pipeline, it means the sum of the value of all opportunities with a close date in the period.  It’s sloppy to say, “pipeline” and then revise to, “oh, I mean current-quarter s3+ pipeline.”  They’re not the same.  Which one are you using when?
  • Pipeline that’s ignored in analytics is usually ignored in operations.  If your company defines “demo” as stage 4 (which you shouldn’t) and measures conversion rates from stage 4, I can guarantee you one thing:   the stage 1-3 pipeline is a garbage dump.   I have literally never met a company that does analytics from stage 3 or stage 4 where this is not true.  As Drucker said, what gets measured, gets managed.  And conversely.  This is bad practice.  All pipeline is valuable.  It should all be inspected, scrubbed, and managed.  That doesn’t happen when you systematically ignore part of it.
  • How do I know if a given $100K opportunity has a real or placeholder value?  You can’t.  Maybe you have a rule that says by stage 3 all values need to be validated, but do you know if that happened?  If you create opportunities with $0 value and say, “don’t enter a value unless it’s socialized with the customer,” then you’ll know.  Otherwise you’ll never be able to tell the difference between a real $100K and a fake one [2].
  • Stage weights should come from regressions, not thin air.  For those regressions to work, stage definitions should come from clear rules.  Then, and only then, can you say things like, “given our (consistent) definition of stage 2 opportunity, we typically see 8% of stage 2 ARR value converted in the current quarter and 9% more converted in the quarter after that.” [3]  Arbitrarily zeroing-out certain stages due to poor pipeline discipline and despite their actual conversion rates is bad practice.

Let’s close with challenging the three answers above:

  • Everybody does it.  Ask your parents about Johnny and bridges.  That’s not a good reason to do the wrong thing when derived from first principles.
  • We want to get people excited.  Good.  How about we get them excited by creating a real pipeline that converts at a healthy rate [4], instead of giving everyone a false sense of security with an inflated big number?
  • We want to be able to compare to (i.e., benchmark against) others who use placeholder values?  Super.  Then create a new metric called “implied pipeline” where you take all the zero-dollar opportunities and substitute an appropriate placeholder value.  You can compare to Johnny without following him off the bridge.

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[1] While stage definitions and conversions vary widely, to make this concrete, here’s one sample funnel that I think is realistic:  stage 1 = BANT, stage 2 = sales accepted with 80% conversion from prior stage, stage 3 = deep dive completed with 80% conversion, stage 4 = solution fit confirmed with 50% conversion, stage 5 = vendor of choice with 60% conversion, stage 6 = win with 80% conversion.  Overall, that implies a s2-to-close rate of 16%, which is in the 10 to 25% range that I typically see.

[2] The hack solution to this is to use $99.999K as the placeholder — i.e., a value that people are unlikely to enter and then ignore that.  Which leads again to the question of why to put fake data into the system only to carefully ignore it in reporting and analytics?  (And hope that you always remember to ignore it.)

[3] This in turn relies on both a consistent definition of close date and a reference to which week of the quarter you’re talking about — such conversion rates vary across the week of the quarter.

[4] One of my CMO friends pointed out that sometimes this “excitement” takes dysfunctional forms — e.g., when sales wants to “cry poor” either to defend a weak forecast or argue for more investment, they can artificially hold oppties at zero value for an extended period (“uninflated balloons”).  This, however, is easily caught when the e-staff is looking at both pipeline (dollar) coverage as well as count (i.e.,  opportunities/rep).

How Much Should You Bet on Educating the Market?

Using the Marketing Fundamental Tension Quadrant to Map Your Demandgen and Communications Strategy

Years ago I wrote a post on what I call the fundamental tension in marketing:  the gap between what we want to say and what our audience wants to hear.

For example, let’s say we’re a supply chain software company.  Our founders are super excited about our AI/ML-based algorithms for demand prediction.  Our audience, on the other hand, barely understands AI/ML [1] and wants to hear about reducing the cost of carrying inventory and matching marketing programs to inventory levels [2].

How then should we market our supply chain software?  Let’s use the following quadrant to help.

Let’s map AI/ML as a marketing message onto this framework.  Do we care about it?  Yes, a lot.  Does our audience?  No.  We’re in Box 4:  we care and they don’t, so we conclude that must therefore educate (as we might dangerously consider them) the unwashed in order to make them care about AI/ML.  We can write a white paper entitled, The Importance of AI/ML in Supply Chain Systems.  We can run a webinar with the same title.  By the way, should we expect a lot of people to attend that webinar?  No.  Why?  Because no one cares.

Market education is hard.  That’s not to say you shouldn’t do it, but realize that you are trying, in a world of competing priorities, to add one to the list and move it up to the top.  It can be done:  digital transformation is widely viewed as business priorities today.  But that took an enormous amount of work from almost the entire software industry.  Your one startup isn’t going to change the VP of Supply Chain’s priorities overnight.

Every good demandgen leader knows it’s far easier to start with things the audience already cares about and then bridge to things your company wants to talk about.  Using the movie theatre metaphor of the prior post, you put “Reduce Inventory Costs” on the marquee and you feature “AI/ML” in a lead role in the movie.

How do you determine those priorities?  I’ll scream it:  MARKET RESEARCH.  You find existing and/or run proprietary market studies targeting your business buyers, asking about their priorities.  Then you create marketing campaigns that bridge from buyer priorities to your messages.  If you’re lucky, you’re in Box 2 and everything aligns without the bridge.  But most software marketers should spend the majority of their time in Box 1, bridging between what’s important to the audience and what’s important to the company.

If you fail to build the bridge in Box 1 you’ll have a webinar full of people of who won’t buy anything.  If you put all your investment into Box 4 you’ll run a lot of empty webinars.

The number one mistake startup marketers make is that they try educate the market on too many things.  You need to care about AI/ML.  And reporting.  And, oh by the way, analytics.  And CuteName.  And features 5, 6, and 7.  And, no, no we’re not feature-driven marketing because we remember to mention benefits somewhere.  We are evangelists.  We are storytellers!

But you’re telling stories that people don’t want to hear.

My rule is simple:  every startup should have one — and only one — Box 4 message and supporting campaigns.  Sticking with our example:

  • We should have a superb white paper on the importance of AI/ML in supply chain systems.
  • We should make claims in our PR boilerplate and About Us page related to our pioneering AI/ML in supply chain systems.
  • We should run a strong analyst relations (AR) program to get thought leaders on board with the importance of AI/ML in supply chain.
  • We should commit to this message for, by marketing standards, an extraordinarily long time; it’s literally a decade-long commitment.  So choose it wisely.

To blast through 30 years of personal industry history:  for Oracle it was row-level locking; for BusinessObjects, the semantic layer; for Endeca, the MDEX engine; for MongoDB, NoSQL [3]; for Salesforce, SaaS (branded as No Software); for Anaplan, the hypercube; for GainSight, customer success; and for Alation, the data catalog [4].

To net out the art of enterprise software marketing, it’s:

  • Stay out of Box 3
  • If you’re lucky, you’re in your Box 2 [5].  Talk about what you want to say because it’s what they want to hear.
  • Spend most of your time in Box 1, bridging from what they want to hear to what you want to say.  This keeps butts in seats at programs and primes them towards your selling agenda.
  • Make one and only one bet in Box 4, use AR to help evangelize it, and produce a small number of very high quality deliverables to tell the story.

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[1] Much as I barely understand a MacPherson strut, despite having been subjected to hearing about it by years of feature-driven automotive marketing.

[2] In other words, “sell what’s on the truck.”  An old example, but likely still true:  the shirt color worn by the model in a catalog typically gets 5x the orders of any other color; so why not do color selection driven by inventory levels instead of graphic design preferences?

[3] Or, as I always preferred, MyNoSQL, simultaneously implying both cheap and easy (MySQL) and document-oriented (NoSQL).  By the way, this claim is somewhat less clear to me than the proceeding two.

[4]  The more the company is the sole pioneer of a category, the more the evangelization is about the category itself.  The more the company emerges as the leader in a competitive market, the more the evangelization is about the special sauce.  For example, I can’t even name a GainSight competitor so their message was almost purely category evangelical.  Alation, by comparison, was close to but not quite a sole pioneer so I wrestled with saying “machine-learning data catalog” (which embeds the special sauce), but settled on data catalog because they were, in my estimation, the lead category pioneer.  See my FAQ for disclaimers as I have relationships past or present with many of the companies mentioned.

[5]  Any space-pioneering application is probably in Box 2.  Any technology platform is almost always in Box 3 or 4.  Any competitive emerging space probably places you in Box 1 — i.e., needing to do a lot of bridging from more generic buyer needs to your special sauce for meeting them.

Seed-Stage Positioning: Lock and Load

With angel and seed money flowing, and a great environment for company creation, I’ve been talking to a lot of seed-stage and pre-seed stage startups of late.  They often ask me about positioning.  Listening to myself talk, I realized that I didn’t really sound like me, and it made me wonder why.

What I Normally Sound Like on Positioning
When people ask me about positioning and messaging, I usually sound like this:

  • As Fausto Coppi said about cycling, positioning is suffering.  The marketer who suffers the most wins.
  • When challenging a marketer in a positioning meeting, the ideal response to every question is: “yes, we thought of that and ruled it out for these reasons.”  You should never be able to come up with something they haven’t thought about already.  Deeply.
  • Positioning is a labor of love.  You need to examine and re-examine all the messages and how they fit together over and over again [1].
  • Slapdash and positioning don’t belong on the same page, let alone the same paragraph or the same sentence.
  • Get Shit Done is the watchword in marketing, today.  There’s no room for perfectionism, except for one thing:  positioning.

In short, I feel about positioning the way David Ogilvy felt about copywriting.

What I Sound Like Talking to Seed-Stage Startups
Lately, in talking with seed-stage startups, however, I’ve heard myself sounding like this:

  • Perfect is the enemy of good.
  • Put in enough thought and build enough consensus that you can execute without wanting to change it every day — but no more than that.
  • Stop worrying about category creation, and worry about proving product-market fit [2].
  • Analysts name categories, not vendors.  Guiding them to the right name is a problem we’ll hopefully get to have in 2-4 years.
  • Just be clear.  The emphasis needs to be 100% on clarity:  make it clear, make it simple, and don’t let confusion interfere.

Think hard but don’t agonize.  Then lock and load.  Debate it, decide it, train the team on it, and then go execute.  Don’t entertain revisiting the positioning unless you get material new information.  Think:  “I’ll write everyone’s concerns down in a Google Doc that we can revisit in two to four quarters — right now we’re in execution mode.” [3]

Why The Difference?
The positioning challenge is fundamentally different between a seed-stage and a larger company.  Managing this difference can be particularly hard for a larger-company director of product marketing who’s just joined their first seed- or early-stage startup.

At a larger company, the product marketer typically works in an existing category and needs to clearly message what their offering does and how it is different from the competition. That often involves amplification of subtle differences in an effort first to position yourself as different and then as better.  You’re trying to differentiate in a market where, to most buyers, everyone sounds the same.  You’re in a why buy mine situation, in a hot and growing market, fighting for share, and in that situation you literally cannot spend enough time and energy getting the optimal answer to the question:  why buy mine?  Anything less than perfect isn’t good enough.

At a seed-stage company you’re trying to see if anyone wants to buy what you’ve built.  Your founder saw a problem and built a solution to it.  But few people, if any, have actually bought it.  You don’t know if they will.  The number one thing your next-round investors will be looking for is how many people didYou’re selling to technology enthusiasts who want to try it because they try everything or, better yet, visionaries who are more than able to map the potential benefits of the product to their business — provided, of course, they understand what the product is.  So your job is simple:  explain what the product is in the clearest simplest, shortest form possible [4].  Anything more than that is wasted effort, better spent on engaging with more people instead of further honing the message.

When seed-stage companies get confused about this, here’s what I think is happening:

  • Perfectionism is winning over pragmatism.  Believe me, I get the desire to want to make it perfect, but in reality you’re just navel gazing.
  • It’s a form of avoidance.  It’s scary that people might fully understand what you built and then say, “no thanks, I don’t need that.”  But that’s precisely what you need to find out.  Relish these conversations, even if reveal that you built the wrong light bulb.  If that’s true, you’ll find out eventually anyway.  Why not fail fast?
  • It’s a failure to understand marketing.  Founders sometimes think that marketing is supposed to dress up their practical but mundane idea so that people will buy it.  That’s wrong.  All that fancy dress-up just interferes with what you should be doing:  finding the right people to hear your idea and clearly telling them what it is. [5] [6]
  • Large-company people not adapting to required small-company practices.

In short, while at larger companies positioning is indeed suffering, at seed-stage companies, positioning is the quick search for simple clarity.

Get it.  Then lock and load.

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[1] Certainly in your own mind, but also with other people and groups:  customers, prospects, sales, product, engineering … and via market research.

[2] Resisting the temptation to expound on category creation, let me say that the podcast episode linked with Stephanie McReynolds on category creation was, I believe, outstanding.  Listen to it for a great discussion on the topic.

[3] But we’re not going to spend hours every week — often just arguing with ourselves — wondering if we’re describing it optimally.

[4] One great way to do that is often via an origin story:  explaining why the founder built it.

[5] Companies often put more energy into what they want to say than who they want to say it to, and that’s a mistake.  Pitching an innovation idea to a conservative buyer might result in rejection, but not because the idea is bad but because the buyer is risk averse. In Geoffrey Moore terms, you want to find visionaries — people who understand technology and can envision how a given technology might solve a range of business problems.

[6] Don’t worry, if you’re talking to the right person (see prior endnote) with a good idea, they’ll tell you the business benefits.  Later in market evolution you’ll need to explain business benefits to people.  But early on, when you’re selling to visionaries, they’ll tell you.