Category Archives: Enterprise

How Much Should You Bet on Educating the Market?

Posted on January 20, 2022 | Leave a comment

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.

# # #

Notes

[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.

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Posted in AR, Demandgen, Enterprise, Marketing, Positioning, SaaS, Sales, Startups, Strategy

Congratulations to Nuxeo on its Acquisition by Hyland

Posted on March 4, 2021 | Leave a comment

It feels like the just the other day when I met a passionate French entrepreneur in the bar on the 15th floor of the Hilton Times Square to discuss Nuxeo.  I remember being interested in the space, which I then viewed as next-generation content management (which, by the way, seemed extraordinarily in need of a next generation) and today what we’d call a content services platform (CSP) — in Nuxeo’s case, with a strong digital asset management angle.

I remember being impressed with the guy, Eric Barroca, as well.  If I could check my notebook from that evening, I’m sure I’d see written:  “smart, goes fast, no BS.”  Eric remains one of the few people who — when he interrupts me saying “got it” — that I’m quite sure that he does.

To me, Nuxeo is a tale of technology leadership combined with market focus, teamwork, and leadership.  All to produce a great result.

Congrats to Eric, the entire team, and the key folks I worked with most closely during my tenure on the board:  CMO/CPO Chris McGlaughlin, CFO James Colquhoun, and CTO Thierry Delprat.

Thanks to the board for having me, including Christian Resch and Nishi Somaiya from Goldman Sachs, Michael Elias from Kennet, and Steve King.  It’s been a true pleasure working with you.

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Posted in Cloud, Enterprise, SaaS, Startups, VC

An Epitaph for Intrapreneurship

Posted on January 26, 2021 | 5 comments

About twenty years ago, before I ran two startups as CEO and served as product-line general manager, I went through an intrapreneurship phase, where I was convinced that big companies should try to act like startups.  It was a fairly popular concept at the time.

Heck, we even decided to try the idea at Business Objects, launching a new analytical applications division called Ithena, with a mission to build CRM analytical applications on top of our platform.  We made a lot of mistakes with Ithena, which was the beginning of the end of my infatuation with the concept:

  • We staffed it with the wrong people.  Instead of hiring experts in CRM, we staffed it largely with experts in BI platforms.  Applications businesses are first and foremost about domain expertise.
  • They built the wrong thing.  Lacking CRM knowledge, they invested in building platform extensions that would be useful if one day you wanted to build a CRM analytical app.  From a procrastination viewpoint, it felt like a middle school dance.  Later, in Ithena’s wreckage, I found one of the prouder moments of my marketing career  — when I simply repositioned the product to what it was (versus what we wanted it to be), sales took off.
  • We blew the model.  They were both too close and too far.  They were in the same building, staffed largely with former parent-company employees, and they kept stock options in both the parent the spin-out.  It didn’t end up a new, different company.  It ended up a cool kids area within the existing one.
  • We created channel conflict with ourselves.  Exacerbated by the the thinness of the app, customers had trouble telling the app from the platform.  We’d have platform salesreps saying “just build the app yourself” and apps salesreps saying that you couldn’t.
  • They didn’t act like entrepreneurs.  They ran the place like big-company, process-oriented people, not scrappy entrepreneurs fighting for food to get through the week.  Favorite example:  they had hired a full-time director of salesops before they had any customers.  Great from an MBO achievement perspective (“check”).  But a full-time employee without any orders to book or sales to analyze?  Say what you will, but that would never happen at a startup.

As somebody who started out pretty enthralled with intrapreneurship, I ended up pretty jaded on it.

I was talking to a vendor about these topics the other day, and all these memories came back.  So I did quick bit of Googling to find out what happened to that intrapreneurship wave.  The answer is not much.

Entrepreneurship crushes intrapreneurship in Google Trends.  Just for fun, I added SPACs to see their relatively popularity.

Here’s my brief epitaph for intrapreneurship.  It didn’t work because:

  • Intrapreneurs are basically entrepreneurs without commitment.  And commitment, that burn the ships attitude, is key part of willing a startup into success.
  • The entry barriers to entrepreneurship, particularly in technology, are low.  It’s not that hard (provided you can dodge Silicon Valley’s sexism, ageism, and other undesirable -isms) for someone in love with an idea to quit their job, raise capital, and start a company.
  • The intrapreneurial venture is unable to prioritize its needs over those of the parent.  “As long as you’re living in my house, you’ll do things my way,” might work for parenting (and it doesn’t) but it definitely does not work for startup businesses.
  • With entrepreneurship one “yes” enables an idea, with intrapreneurship, one “no” can kill it.  What’s more, the sheer inertia in moving a decision through the hierarchy could kill an idea or cause a missed opportunity.
  • In terms of the ability to attract talent and raise capital, entrepreneurship beats intrapreneurship hands down.  Particularly today, where the IPO class of 2020 raised a mean of $350M prior to going public.

As one friend put it, it’s easy with intrapreneurship to end up with all the downsides of both models.  Better to be “all in” and redefine the new initiative into your corporate self image, or “all out” and spin it out as an independent entity.

I’m all for general mangers (GMs) acting as mini-CEOs, running products as a portfolio of businesses.  But that job, and it’s a hard one, is simply not the same as what entrepreneurs do in creating new ventures.  It’s not even close.

The intrapreneur is dead, long live the GM.

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Posted in Enterprise, Entrepreneurship, Leadership, Management, Silicon Valley, Startups, Strategy

The Holy Grail of Enterprise Sales: Is a Repeatable Sales Process Enough?

Posted on January 14, 2021 | Leave a comment

(This is the third in a three-part restructuring and build-out of a previous post.  See note [1] for details.)

In the first two posts in this series, we first defined a repeatable sales process and then discussed how to prove that your sales process is repeatable.

All that was just the warm-up for the big idea in this series:  is repeatability enough?

The other day I was re-reading my favorite book on data governance (and yes I have one), Non-Invasive Data Governance by Bob Seiner.  Reading it reminded me of the Capability Maturity Model, from Carnegie Mellon’s Software Engineering Institute.

Here’s the picture that triggered my thinking:

Did you see it?  Look again.

Repeatable is level two in a five-level model.  Here we are in sales and marketing striving to achieve what our engineering counterparts would call 40% of the way there.  Doesn’t that explain a lot?

To think about what we should strive for, I’m going to switch models, to CMMI, which later replaced CMM.   While it lacks a level called “repeatable” – which is what got me thinking about the whole topic in the first place – I think it’s nevertheless a better model for thinking about sales [2].

Here’s a picture of CMMI:

I’d say that most of what I defined as a repeatable sales process fits into the CMMI model as level 3, defined.  What’s above that?

  • Level 4, quantitively managed. While most salesforces are great about quantitative measurement of the result – tracking and potentially segmenting metrics like quota performance, average sales price, expansion rates, win rates – fewer actually track and measure the sales process [3].  For example, time spent at each stage, activity monitoring by stage, conversion by stage, and leakage reason by stage.  Better yet, why just track these variables when you can act on them?  For example, put rules in place to take squatted opportunities from reps and give them to someone else [4], or create excess stage-aging reports that will be reviewed in management meetings.
  • Level 5, optimizing. The idea here is that once the process is defined and managed (not just tracked) quantitatively, then we should be in a mode where we are constantly improving the process.  To me, this means both analytics on the existing process as well as qualitative feedback and debate about how to make it better.  That is, we are not only in continual improvement mode when it comes to sales execution, but also when it comes to sale process.  We want to constantly strive to execute the process as best we can and also strive to improve the process.  This, in my estimation, is both a matter of culture and focus.  You need a culture that process- and process-improvement-oriented.  You need to take the time – as it’s often very hard to do in sales – to focus not just on results, but on the process and how to constantly improve it.

To answer my own question:  is repeatability enough?  No, it’s not.  It’s a great first step in the industrialization of your sales process, but it quickly then becomes the platform on which you start quantitative management and optimization.

So the new question should be not “is your sales process repeatable?” but “is it optimizing?”  And never “optimized,” because you’re never done.

# # #

Notes

[1] I have a bad habit, which I’ve been slowly overcoming, to accidently put real meat on one topic into an aside of a post on a different one.  After reading the original post, I realized that I’d buried the definition of a repeatable sales model and the tests for having one into a post that was really about applying CMMI to the sales model.  Ergo, as my penance, as a service to future readers, and to help my SEO, I am decomposing that post into three parts and elaborating on it during the restructuring process.

[2] The nuance is that in CMM you could have a process that was repeatable without being (formally) defined.  CMMI gets rid of this notion which, for whatever it’s worth, I think is pretty real in sales.  That is, without any formal definition, certain motions get repeated informally and through word of mouth.

[3] With the notable exception of average sales cycle length, which just about everyone tracks – but this just looks at the whole process, end to end.  (And some folks start it late, e.g., from-demo as opposed to from-acceptance.)

[4] Where squatting means accepting an opportunity but not working on it, either at all or sufficiently to keep it moving.

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Posted in Enterprise, Sales, Sales Model, Startups

The Holy Grail of Enterprise Sales: Proving a Repeatable Sales Process

Posted on January 14, 2021 | 1 comment

(This is the second in a three-part restructuring and build-out of a previous post.  See note [1] for details.)

In the prior post we introduced repeatable sales process as the Holy Grail of enterprise software sales and, unlike some who toss the term around rather casually, we defined a repeatable sales process as meaning you have six things:

  1. Standard hiring profile
  2. Standard onboarding program
  3. Standard support ratios
  4. Standard patch
  5. Standard kit
  6. Standard sales methodology

The point of this, of course, is to demonstrate that given these six standard elements you can consistently deliver a desirable, standard result.

The surprisingly elusive question is then, how to measure that?

  • Making plan?  This should be a necessary but not sufficient condition for proving repeatability.  As we’ll see below, you can make plan in healthy as well as unhealthy ways (e.g., off a small number of reps, off disproportionate expansion and weak new logo sales).
  • Realizing some percentage of your sales capacity?  I love this — and it’s quite useful if you’ve just lost or cut a big chunk of your salesforce and are ergo in the midst of a ramp reset — but it doesn’t prove repeatability because you can achieve it in both good and bad ways [2].
  • Having 80% of your salesreps at 100%+ of quota?  While I think percent of reps hitting quota is the right way to look at things, I think 80% at 100% is the wrong bar.

Why is defaulting to 80% of reps at 100%+ of quota the wrong bar?

  • The attainment percentage should vary as function of business model: with a velocity model, monthly quotas, and a $25K ARR average sales price (ASP), it’s a lot more applicable than with an enterprise model, annual quotas, and a $300K ASP.
  • 80% at 100%+ means you beat plan even if no one overperforms [3] – and that hopefully rarely happens.
  • There is a difference between annual and quarterly performance, so while 80% at 100% might be reasonable in some cases on an annual basis, on a quarterly basis it might be more like 50% — see the spreadsheet below for an example.
  • The reality of enterprise software is that performance is way more volatile than you might like it to be when you’re sitting in the board room
  • When we’re looking at overall productivity we might look at the entire salesforce, but when we’re looking at repeatability we should look at recently hired cohorts. Does 80% of your third-year reps at quota tell you as much about repeatability – and the presumed performance of new hires – as 80% of your first-year reps cohort?

Long story short, in enterprise software, I’d say 80% of salesreps at 80% of quota is healthy, providing the company is making plan.  I’d look at the most recent one-year and two-year cohorts more than the overall salesforce.  Most importantly, to limit survivor bias, I’d look at the attrition rate on each cohort and hope for nothing more than 20%/year.  What good is 80% at 80% of quota if 50% of the salesreps flamed out in the first year?  Tools like my salesrep ramp chart help with this analysis.

Just to make the point visceral, I’ll finish by showing a spreadsheet with a concrete example of what it looks like to make plan in a healthy vs. unhealthy way, and demonstrate that setting the bar at 80% of reps at 100% of quota is generally not realistic (particularly in a world of over-assignment).

If you look at the analysis near the bottom, you see the healthy company lands at 105% of plan, with 80% of reps at 80%+ of quota, and with only 40% of reps at 100%+ of quota.  The unhealthy company produces the same sales — landing the company at 105% of plan — but due to a more skewed distribution of performance gets there with only 47% of reps at 80%+ and only a mere 20% at 100%+.

In our final post in this series, we’ll ask the question:  is repeatability enough?

# # #

Notes

[1] I have a bad habit, which I’ve been slowly overcoming, to accidently put real meat on one topic into an aside of a post on a different one.  After reading the original post, I realized that I’d buried the definition of a repeatable sales model and the tests for having one into a post that was really about applying CMMI to the sales model.  Ergo, as my penance, as a service to future readers, and to help my SEO, I am decomposing that post into three parts and elaborating on it during the restructuring process.

[2] Unless you’ve had either late hiring or unexpected attrition, 80% of your notional sales capacity should roughly be your operating plan targets.  So this is point is normally subtly equivalent to the prior one.

[3] Per the prior point, the typical over-assignment cushion is around 20%

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Posted in Enterprise, GTM, Marketing, Sales, Sales Model, Salesops, Startups