Category Archives: Marketing

What a Pipeline Coverage Target of >3x Says To Me

I’m working with a lot of different companies these days and one of the perennial topics is pipeline.

One pattern I’m seeing is CROs increasingly saying that they need more than the proverbial 3x pipeline coverage ratio to hit their numbers [2] [3].  I’m hearing 3.5x, 4x, or even 5x.  Heck — and I’m not exaggerating here — I even met one company that said they needed 100x.  Proof that once you start down the >3x slippery slope that you can slide all the way into patent absurdity.

Here’s what I think when a company tells me they need >3x pipeline coverage [4]:

  • The pipeline isn’t scrubbed.  If you can’t convert 33% of your week 3 pipeline, you likely have a pipeline that’s full of junk opportunities (oppties). Rough math, if 1/3rd slips or derails [5] [6] and you go 50-50 on the remaining 2/3rds, you convert 33%.
  • You lose too much.  If you need 5x pipeline coverage because you convert only 20% of it, maybe the problem isn’t lack of pipeline but lack of winning [7].  Perhaps you are better off investing in sales training, improved messaging, win/loss research, and competitive analysis than simply generating more pipeline, only to have it leak out of the funnel.
  • The pipeline is of low quality.  If the pipeline is scrubbed and your deal execution is good, then perhaps the problem is the quality of pipeline itself.  Maybe you’re better off rethinking your ideal customer profile and/or better targeting your marketing programs than simply generating more bad pipeline [8].
  • Sales is more powerful than marketing.  By (usually arbitrarily) setting an unusually high bar on required coverage, sales tees up lack-of-pipeline as an excuse for missing numbers.  Since marketing is commonly the majority pipeline source, this often puts the problem squarely on the back of marketing.
  • There’s no nurture program.  Particularly when you’re looking at annual pipeline (which I generally don’t recommend), if you’re looking three or four quarters out, you’ll often find “fake opportunities” that aren’t actually sales opportunities, but are really just attractive prospects who said they might start an evaluation later.  Are these valid sales opportunities?  No.  Should they be in the pipeline?  No.  Do they warrant special treatment?  Yes.   That should ideally be accomplished by a sophisticated nurture program. But lacking that, reps can and should nurture accounts.  But they shouldn’t use the opportunity management system to do so; it creates “rolling hairballs” in the pipeline.
  • Salesreps are squatting.  The less altruistic interpretation of fake long-term oppties is squatting.  In this case, a rep does not create a fake Q+3 opportunity as a self-reminder to nurture, but instead to stake a claim on the account to protect against its loss in a territory reorganization [9].   In reality, this is simply a sub-case of the first bullet (the pipeline isn’t scrubbed), but I break it out both to highlight it as a frequent problem and to emphasize that pipeline scrubbing shouldn’t just mean this- and next-quarter pipeline, but all-quarter pipeline as well [10].

# # #

Notes

[1] e.g., from marketing, sales, SDRs, alliances.  I haven’t yet blogged on this, and I really need to.  It’s on the list!

[2] Pipeline coverage is ARR pipeline divided by the new ARR target.  For example, if your new ARR target for a given quarter is $3,000K and you have $9,000K in that-quarter pipeline covering it, then you have a 3x pipeline coverage ratio.  My primary coverage metric is snapshotted in week 3, so week 3 pipeline coverage of 3x implies a 33% week three pipeline conversion rate.

[3] Note that it’s often useful to segment pipeline coverage.  For example, new logo pipeline tends to convert at a lower rate (and require higher coverage) than expansion pipeline which often converts at a rate near or even over 100% (as the reps sometimes don’t enter the oppties until the close date — an atrocious habit!)  So when you’re looking at aggregate pipeline coverage, as I often do, you must remember that it works best when the mix of pipeline by segment and the conversion rate of each segment is relatively stable.  The more that’s not true, the more you must do segmented pipeline analysis.

[4] See note 2.  Note also the ambiguity in simply saying “pipeline coverage” as I’m not sure when you snapshotted it (it’s constantly changing) or what time period it’s covering.  Hence, my tendency is to say “week 3 current-quarter pipeline coverage” in order to be precise.  In this case, I’m being a little vague on purpose because that’s how most folks express it to me.

[5] In my parlance, slip means the close date changes and derail means the project was cancelled (or delayed outside your valid opportunity timeframe).  In a win, we win; in a loss, someone else wins; in a derail, no one wins.  Note that — pet peeve alert — not making the short list is not a derail, but a loss to as-yet-known (so don’t require losses to fill in a single competitor and ensure missed-short-list is a possible lost-to selection).

[6] Where sales management should be scrubbing the close date as well as other fields like stage, forecast category, and value.

[7] To paraphrase James Mason in The Verdict, salesreps “aren’t paid to do their best, they’re paid to win.”  Not just to have a 33% odds of winning a deal with a three-vendor short list.  If we’re really good we’re winning half or more of those.

[8] The nuance here is that sales did accept the pipeline so it’s presumably objectively always above some quality standard.  The reality is that pipeline acceptance bar is not fixed but floating and the more / better quality oppties a rep has the higher the acceptance bar.  And conversely:  even junk oppties look great to a starving rep who’s being flogged by their manager to increase their pipeline.  This is one reason why clear written definitions are so important:  the bar will always float around somewhat, but you can get some control with clear definitions.

[9] In such cases, companies will often “grandfather” the oppty into the rep’s new territory even if it ordinarily would not have been included.

[10] Which it all too often doesn’t.

What is a Minimum Viable Product, Anyway? My Favorite MVP Analogy.

The concept of minimum viable product (MVP) has been popularized in the past decade thanks to the success of the wonderful book, The Lean Startup.  It’s thrown around so casually, and you hear it so often, that sometimes you wonder how — or even if — people define it.

In this post, I’ll describe how I think about MVPs, first using one real-life example and then using my favorite MVP analogy.

The concept of a minimum viable product is simple:

  • Every startup is basically a hypothesis (e.g., we think people will buy an X).
  • Instead of doing a big build-up during a lengthy stealth phase concluding in a triumphant (if often ill-fated) product unveiling, let’s build and ship something basic quickly — and start iterating.
  • By taking this lean approach we can test our hypothesis, learn, and iterate more quickly — and avoid tons of work and waste in the process.

The trick is, of course, those two pesky words, minimum and viable.  In my worldview:

  • Minimum means the least you can do to test your hypothesis.
  • Viable means the product actually does the thing it’s supposed to do, even in some very basic way.

I’ll use an old, but concrete, example of an MVP from my career at Business Objects.  It’s the late 1990s.  The Internet is transforming computing.  We sell a high-functionality query & reporting tool, capable of everything from ad hoc query to complex, highly-formatted reports to interactive multidimensional analysis.  That tool is a client/server Windows application and we need to figure out our web strategy.  We are highly constrained technologically, because it’s still the early days of the web browser (e.g., browsers had no print functionality) [1].

After much controversy, John Ball and the WebIntelligence team agreed on (what we’d now call) the following MVP:

  • A catalog of reports that users can open/browse
  • End-user ad hoc query
  • Production of very basic tabular reports
  • Semi-compatibility with our existing product [2]

But it would work in a browser without any plug-ins, web native.  No multi-block reports.  No pages.  No printing.  No interactive analysis.  No multidimensional analysis.  No charting.  No cross-tabs.  No headers, no footers.  Effectively, the world’s most basic reporting tool — but it let users run an ad hoc query over the web and produce a simple report.  That was the MVP.  That was the hypothesis — that people would want to buy that and evolve with us over time.

Because of that tightly focused MVP we were able to build the product quickly, position it clearly within the product line [3], and eventually use it as the basis for an entirely new line of business [4].

Now, let’s do the analogy.  Pretend for a moment we’re in a world where there are no four-wheel drive cars.  We have invented the four-wheel drive car.  We imagine numerous use-cases [5] and a big total available market (TAM).

What should be our MVP?  Meet the 1947 Jeep Willys [6] [7].

No roof.  No back seat.  In some cases, no windscreen.  No doors.  No air conditioning.  No entertainment system.  No navigation.  No cup holders.  No leather.  No cruise control.  No rearview camera.  No ABS.  No seatbelts.  No airbags.

No <all that shit that too many product managers say are requirements because they don’t understand what MVP means>.

Just the core:  a seat, a steering wheel, an engine, a transmission, a clutch, and four traction tires.

  • Is it missing all kinds of functionality?  Yes
  • In this case, would it even be legal to sell?  No.  Well, maybe off-road, but we’re in analogy-mode here.
  • But can it get you across a muddy field or down a muddy road?  YES.

And that’s the point.  It’s minimum because it’s missing all kinds of things we can easily imagine people wanting, later.  It’s viable because it does the one thing that no other car does.  So if you need to cross a muddy field or go down a muddy road, you’ll buy one.

As Steve Blank says:  “You’re selling the vision and delivering the minimum feature set to visionaries, not everyone” [8]. 

So next time you think someone is focused on jamming common but non-core attributes into an MVP, tell them they’re counting cupholders in a Willys and point them here.

# # #

Notes

[1] And printing is a pretty core requirement for a reporting application!

[2] This was key.  WebIntelligence could not even open a BusinessObjects report.  Instead, we opted for compatibility one layer deeper, at the semantic layer (that defined data objects and security) not the reporting layer.

[3] If you want all that power, use BusinessObjects.  If you want web native, use WebIntelligence.  And you can share semantic layer definitions and security.

[4] BI extranets.

[5] From military off-road applications to emergency off-road and/or slippery conditions to sand recreational to family vehicles on snow and many  more.

[6] Which in some ways literally was the MVP for Jeeps.

[7] Popularized by the Grateful Dead in Sugar Magnolia (“… jump like a Willys in four-wheel drive.”)

[8] Where I’ll define visionary as someone who has the problem we’re trying to solve and willing to use a new technology to solve it.  It’s a little easier to think of someone trying a next-generation database system as a “technology visionary” than the Army buying a Jeep, but it’s the same characteristic.  They need a currently unsolvable problem solved, and are willing to try unconventional solutions to do it.

Why I’m Advising Bluecore

I first read The One to One Future by Don Peppers and Martha Rogers in 1997, four years after it was published.  As a marketer, the book made a big impression on me.  It was revolutionary stuff:  we should make the paradigm shift from mass marketing to individualized marketing.

When the book was published in 1993, newspaper ads were $75B/year, TV around $60B, the web browser was a mere three years old, and there were 623 total sites on the web.  There was effectively no web advertising market.  It was nine years before the Minority Report popularized a future vision of one-to-one advertising.  It was six years before Paco Underhill published Why We Buy revealing insights gleaned by manually tracking shoppers to understand in-store behavior [1].

Look at the subtitle: “Building Relationships One Customer at a Time.” You could use that in a webinar today.  The One to One Future was not just ahead of its time; it was so far ahead of its time that it could have equally been categorized under either “marketing” or “science fiction.”

Why?

  • It turns out, as with science fiction, that it’s easier to envision something than to build it. Remember, “they promised us flying cars and we got 140 characters.” [2]
  • Building individualized marketing systems required layers and layers of underpinnings that were simply not in place. You can’t do good personalization without a clean, real-time, 360-degree view of your customer.  Clean means a big effort into data quality and data profiling and typically either master data management or a customer data platform [3].  Real-time means real-time data integration [4].  360-degrees means pulling relevant data from virtually all of your systems.  Self-driving cars don’t work on cow paths.  Building those layers of requisite infrastructure has taken decades.
  • Marketing’s focus on the perfect offer was flawed. Say I found an offer with an 90% chance that you’d respond affirmatively.  Perfect, right?  But it was for a product that was out of stock.  The perfect offer has to be for the right product, in the customer’s preferred size or color, and available to sell.  We can’t just find the set called {great offers}.  We needed to intersect it with the set called {in stock and need to sell}.  This made a hard problem harder by pulling inventory and the supply chain into the equation.
  • Marketers got trapped in a vicious downward cycle of communications. Email click rates have nearly been cut in half over the past decade.  Marketing’s solution?  Send more emails to make up the difference.  Email vendors, who typically price by the email, were only too happy to accommodate.  That, however, is a short-term mentality.  More bad email with lower open and click rates isn’t the solution.  The same holds for ads and promotions.  Marketing needs to get out of this race to the bottom.  We need to focus on quality, not quantity.  And pay vendors for performance delivered, not communications sent, while we’re at it.
  • Finally, the retail industry needed to shift mentality from store-first to digital-first. Roots, as they say, run deep and retailers have long, deep roots in physical stores.  Bricks-and-mortar supposedly changed to clicks-and-mortar, but really, it was mortar-and-clicks the whole time.  The industry never really changed to digital-first from store-first.  Until Covid-19, that is.  While this meme, popularized in Forbes, was intended for many industries, it could have been custom made for retail [5].

So where does Bluecore fit in?

  • Bluecore is a multi-channel personalization platform. They’re building what marketers in the past dreamed of, but couldn’t build, because the infrastructure wasn’t there.  Now it can be built, and they’re building it.
  • Bluecore is an AI/ML company focused on retail analytics and personalization. I’ve blogged before that AI/ML is best applied to specific problems and not general ones, and this is a great example.  They are a closed-loop, retailed-focused application that gets smarter every day and with each new customer.  If you believed in the increasing returns of marketing leadership in technology markets before AI/ML [6], you should believe in them twice as much after.
  • Bluecore’s personalization understands both customer and product – and intersects them. Across a catalog of more than 250M products and SKUs, Bluecore can match customers and products at a 1-1 level.  It automates what would have been the work of a team of in-house data scientists.
  • Bluecore is paid for performance, not volume. They back up their performance claims with a pricing model based not on volume but on success.  This is a great example of superior technology enabling disruptive business model innovation.

Why am I advising Bluecore?  Three reasons:

  • As a true, blue marketer this stuff genuinely interests me. I love working with marketing companies on marketing problems.
  • It’s always about the team. I’ve loved working with Fayez Mohamood (founder/CEO) and Sherene Hilal (SVP of Marketing).  As a bonus, former Salesforce teammate Scott Beechuk is an investor and on the board.  I like working with people who like working with me and appreciate my inimitable (I inadvertently almost typed inimical) style when it comes to feedback.
  • The momentum and market opportunity. Bluecore’s a highly successful company, having raised over $100M in VC with top-tier investors, and they are pursuing transformational change in a $4T market.  The last 100 years in retail were all about stores, the next 100 will be about retailers meeting customers wherever they are.  And that’s what Bluecore does.

# # #

Notes
[1] And why, to this day, you can find still baskets strewn throughout many retail shops as opposed to only at the entrance.  His work was kind of a manual predecessor to systems like RetailNext, whose founder I got to know through mutual investments in a prior life from StarVest.

[2]  Peter Thiel at Yale.

[3] Which weren’t to be invented for about 20 years

[4] The data warehouse was invented in 1992, with the publication of Bill Inmon’s Building the Data Warehouse.   Ralph Kimball would invent the star schema 4 years after that.

[5] Apologies to frequent readers for using this meme again – but I just love it!

[6] Tech buyers, and particularly IT buyers, tend to face high opportunity costs and high switching costs and are ergo generally risk averse.  This drives increasing returns for early market leaders.  Think:  no one ever got fired for buying IBM.

What To Do When You Need Pipeline in a Hurry

It’s that time of year, I suppose.  You’ve hopefully approved your 2021 operating plan by now — even if you’re on an increasingly popular 1/31 fiscal year end.  You’ve signed up for some big numbers to meet your aggressive goals (and fund those aggressive spending plans).  And now you might well be thinking one thing:

“Oh shit, we need some pipeline.  Fast.”

To really help you — in the long-term — we’ll need to have a stern talking to about driver-based planning, sales capacity models (particularly if you’re upside-down [1] on sales capacity), inverted funnel models to calculate the demandgen budget, and time-based closed rates to forecast conversion from your existing pipeline (and, I’ve increasingly seen, conversion from to-be-generated pipeline [2]).

And we’ll also need to review the seven words Mike Moritz said to me when I started as CEO of MarkLogic:  “make a plan that you can beat.”

But, I hear you thinking:  that all sounds great and I’m sure I should do it one day — but right now I have a problem.  I need some pipeline, fast.

Got it.  So here are three high-level things you need to do:

  1. Declare general quarters — all hands to battle stations.  You should never waste a good crisis, so call an all-hands meeting, start it with this audio file, and tell everyone you want them working on the problem.  You want zero complacency [3] or fatalism:  we don’t need people cueing the quartet to play Nearer My God To Thee [3a] when there are still lots of things we can do to affect the outcome.
  2. Focus on winning the opportunities you can win.  You think you need pipeline, but what you actually need is the new ARR that comes from it.  Let’s not forget that.  In math terms, we’re going to need high to record-high conversion of the opportunities (oppties) that are in the pipeline today.  So let’s put sales and executive management attention on identifying the winnable oppties and fighting like never before to win them — including potentially re-assigning your best oppties to your best reps [4].
  3. Focus on finding new opportunities that move fast.  Remember that nine-month sales cycle is an average; some opportunities close a lot faster.  Expansion oppties tend to move a lot faster than new logo oppties.  SMB oppties tend to move faster than enterprise ones.  Get salesops to figure out which ones move faster for you — remember you don’t need just any pipeline, you need fast-moving (and high-converting) pipeline.

In addition, if you’re not doing it already, you need marketing to start forecasting next-quarter’s day-one pipeline as of about week 3 of the current quarter, so we can increase our lead time on finding out about these problems next time.

Now, let’s dive a bit deeper into ways to accelerate existing pipeline and how to generate new, fast-moving pipeline when you need some more.

Pipeline Acceleration Tactics
Here is a list of common pipeline patterns and how you can use them and/or workaround them to accelerate your pipeline.

  • Expansion pipeline moves faster than new logo pipeline.  So have AEs, CSMs, or SDRs contact existing customers to discuss expansion opportunities.
  • It’s easier to accelerate planned expansions than create new ones.  Look at out-quarter expansion pipeline and have AEs reach out to customers to discuss moving them forward and/or offering incentives to do so.
  • Partner-sourced pipeline usually moves faster than marketing- or sales-sourced pipeline.  It also typically closes at a higher rate.  Now is a great time to sit down with partners to review opportunities and see what can be accelerated and what incentives you can offer them to help out.
  • Proofs of concept (POCs) stall oppties in the pipeline.  To remove them from your sales cycle try to substitute highly relevant customer references as alternative proof.  It’s a win/win:  you get your deal faster and the customer gets the benefits of your system faster.  Alternatively, reduce the customer’s need for up-front proof by offering a back-end guarantee [5].  Either way, we might be able to cut 90+ days out of your sales cycle.
  • Reheated, old pipeline often moves faster than new.  I’ve often quipped that the best patch in the company is the no-decision pile [6].  Now is a great time to have AEs and SDRs call up no-decision oppties.  “So, whatever happened with that evaluation you were doing?”  Hey, while we’re at it, let’s call up lost oppties as well.  “So, did you end up buying from Badco?  How’d that work out?”  Both types of reheated oppties have the potential to move faster than net new ones.
  • SDRs can delay entry into the pipeline.  We love our SDRs and they’re great for funnel optimization when times are good.  But when times are tough, selectively cut them out of the loop [7].  For example, make a rule that says for accounts of size X (or on list Y), when we get a contact with title Z, pass them directly to the salesrep.  Not only might you accelerate pipeline entry by a week or two, but the AE will likely do a better job in discovery.
  • Legal can stall you out on the two-yard line.  Get your legal team involved in your red zone offense by creating a fast-turn version of your contract that contains only your minimum required terms.  Then inform the customer that you’re giving them toned-down paperwork and incent them to turn quickly with you on signing it [8].

Techniques to Generate New, Fast-Moving Pipeline
When nothing other than net new pipeline will do, then here are some things you can do:

  • Run marketing campaigns to find existing evaluations.  If you can’t make your own party, then why not sneak into someone else’s?  Run a webinar entitled, “How to Evaluate a Blah” or “Five Things to Look for in a Blah.”  Record and transcribe it to get draft 1 of an e-book you can use as a gated asset.
  • Use search advertising to find existing evaluations.  Buy competitive search terms (brand names), evaluation-related search terms (“how to evaluate”), comparison search terms (e.g., “Gong vs. Chorus,” “Oracle alternatives”), or late-funnel search terms (e.g., “Clari pricing”).
  • Look for warm accounts, not just warm contacts.  Sometimes you can see more if you step back a bit.  Instead of looking at the lead/contact level, do an analysis of which accounts have high levels of activity across all their contacts.  That might be a good clue there’s an evaluation happening or starting.
  • Buy intent data. Several vendors — including 6Sense, Bombora, Demandbase, G2, TechTarget, and Zoominfo — look for data that signals companies are investigating given product categories.  Let someone else do the company-finding for you and then market to (and/or SDR outbound call) them.
  • Buy meetings.  While I’ve always heard mixed reviews about appointment-setting firms, I also know they’re a go-to resource when you’re in trouble — particularly if you’re bottlenecked up-funnel in marketing or SDRs.  Consider a service like Televerde or By Appointment Only.  While these vendors started out in appointment-setting, both have broadened into more full-service demand generation that can help you in many ways.
  • Stalk old customers in new jobs.  Applications like UserGems let you track customers as they change jobs.  What could be faster than selling an existing happy customer when they’re in a new position?  It won’t hit every time (e.g., if they already have and are happy with another system), but they’re certainly leads that can turn into fast-moving pipeline.  You can do roughly the same thing yourself manually with LinkedIn Sales Navigator.
  • Do LinkedIn targeted advertising.   I’m always surprised how many colleagues say LinkedIn doesn’t work that well despite its superior targeting abilities.  Perhaps that’s like anglers saying the “fishing is OK” regardless of  the action.  If you know who to target and think that target can move fast, then go for it.
  • Call blitzes.  Remember we said to never waste a good crisis.  It’s a great time to set up dedicated call blitzes to prospects or existing customers.  Just make sure we know who’s blitzing whom so the same person doesn’t get hit by an AE, an SDR, and a CSM all at once.
  • Contests and prizes.  Finally, why not make it fun?!  Nothing gets the sales blood flowing like competition and incentives.

Hopefully these ideas stimulated some thoughts to help you get the pipeline you need.  And, even more hopefully, realize that we should build many of these now-crisis activities as healthy habits going forward.

# # #

Notes
[1] Meaning that your plan number is larger than your sales productivity capacity.  An undesirable, but certainly not unheard of, situation.

[2] As I’m increasingly seeing time-based closed rates used, something to my surprise.  I’d really created the technique for short- to mid-term gap analysis.  I generally make an marketing budget purely off an inverted funnel model.  But that said, using time-based closed rates by pipeline source would be more accurate.

[3] If for no other reason to avoid the common fallacious complacency of “well, with a nine-month sales cycle, if we’re short of pipeline now there’s nothing we can do, so let’s just accept that we’re going to hit the iceberg.

[3a] While I make light of it in the post, it’s actually both an amazing and touching story.  “Sometime around 2:10 a.m. as the Titanic began settling more quickly into the icy North Altantic, the sounds of ragtime, familiar dance tunes and popular waltzes that had floated reassuringly across her decks suddenly stopped as Bandmaster Wallace Hartley tapped his bow against his violin. Hartley and his musicians, all wearing their lifebelts now, were standing back at the base of the second funnel, on the roof of the First Class Lounge, where they had been playing for the better part of an hour. There were a few moments of silence, then the solemn strains of the hymn “Nearer My God to Thee” began drifting across the water. It was with a perhaps unintended irony that Hartley chose a hymn that pleaded for the mercy of the Almighty, as the ultimate material conceit of the Edwardian Age, the ship that “God Himself couldn’t sink,” foundered beneath his feet.”  Hartley concluded in saying, “Gentlemen, it has been a privilege playing with you tonight.”

[4] Most compensation plans allow midstream territory changes and while moving oppties from bad reps to good reps cuts against the grain for most sales managers, well, we are in an emergency, andd we all know that the odds of an oppty closing are highly related to who’s working on it.  Perhaps soften the sting by uplifting and then splitting the quota.  Or just fire the bad rep.  But win the deal.

[5] Introduce a 90- or 120-day acceptance clause.  This will likely have accounting and/or bookings policy ramifications, but we are in an emergency.  Better to hit your target with a few customers on acceptance (especially if you’re sure you can deliver against the criteria) than to miss.

[6] That is, the oppties that were marked by their owners as neither won nor lost, but no decision.  Sometimes also called derailed oppties.  If you have discipline about reason codes you can find the right ones even faster.

[7] Perhaps using the freed-up time to prospect within the installed base, if your CSMs are not salesy.  Or doing longer-shot outbound into named accounts.

[8] I’m a little dusty legally, but the ultimate form of this was a clickwrap which, in a pinch, was sometimes used (with the consent of the customer) to work around the customer’s oft-bottlenecked legal department and get a baseline agreement in place that can later be revised or replaced.

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

(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?

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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%

The Holy Grail of Enterprise Sales: Defining the Repeatable Sales Process

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

The number one question go-to-market question in any enterprise software startup is:  “do you have a repeatable sales process?” or, in more contemporary Silicon Valley patois, “do you have a repeatable sales motion?”

It’s one of the key milestones in startup evolution, which proceed roughly like:

  • Do you have a concept?
  • Do you have a working product?
  • Do you have any customer traction (e.g., $1M in ARR)?
  • Have you established product-market fit?
  • Do you have a repeatable sales process?

Now, when pressed to define “repeatable sales process,” I suspect many of those asking might reply along the same lines as the US Supreme Court in defining pornography:

“I shall not today attempt further to define the kinds of material I understand to be embraced… but I know it when I see it …”

That is, in my estimation, a lot of people throw the term around without defining it, so in the Kelloggian spirit of rigor, I thought I’d offer my definition:

A repeatable sales process means 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

All of which contribute to delivering a desirable, standard result.  Let’s take a deeper look at each:

  1. You hire salesreps with a standard hiring profile, including items such as years of experience, prior target employers or spaces, requisite skills, and personality assessments (e.g., DiSC, Hogan, CCAT).
  2. You give them a standard onboarding program, typically built by a dedicated director of sales productivity, using industry best practices, one to three weeks in length, and accompanied by ongoing clinics.
  3. You have standard support ratios (e.g., each rep gets 1/2 of a sales consultant, 1/3 of an SDR, and 1/6 of a sales manager).  As you grow, your sales model should also use ratios to staff more indirect forms of support such as alliances, salesops, and sales productivity.
  4. You have a standard patch (territory), and a method for creating one, where the rep can be successful.  This is typically a quantitative exercise done by salesops and ideally is accompanied by a patch-warming program [2] such that new reps don’t inherit cold patches.
  5. You have standard kit including tools such as collateral, presentations, demos, templates.  I strongly prefer fewer, better deliverables that reps actually know how to use to the more common deep piles of tools that make marketing feel productive, but that are misunderstood by sales and ineffective.
  6. You have a standard sales methodology that includes how you define and execute the sales process.  These include programs ranging from the boutique (e.g., Selling through Curiosity) to the mainstream (e.g., Force Management) to the classic (e.g., Customer-Centric Selling) and many more.  The purpose of these programs is two-fold:  to standardize language and process across the organization and to remind sales — in a technology feature-driven world — that customers buy products as solutions to problems, i.e., they buy 1/4″ holes, not 1/4″ bits.

And, most important, you can demonstrate that all of the above is delivering some desirable standard result, which will be the topic of the next post.

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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.  My favorite example:  it took me ~15 years to create a post on my marketing credo (marketing exists to make sales easier) despite mentioning it in passing in numerous posts.  After reading the prior 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] I think of patch-warming as field marketing for fallow patches.  Much as field marketing works to help existing reps in colder patches, why can’t we apply the same concepts to patches that will soon be occupied?  This is an important, yet often completely overlooked, aspect of reducing rep ramping time.

The Key to Branding Success: Staying in Character

Decades ago I had the pleasure of watching a branding video, created by a San Francisco ad agency, narrated by an advertising executive with a familiar voice who’d narrated scores of commercials [1].  It was, I believe, entitled Staying in Character and while I’ve searched the internet for it many times over the years — and just spent another hour unsuccessfully trying again — I’ve never managed to find it.

The video talked about the importance of brands staying in character in their marketing and advertising.  Sadly, nowadays, when you search for “brands staying in character,” you’re more likely to come up with an article about mascots than one about brand character.

All these thoughts were stirred up the other morning when I read this story about Hugh Grant.

Staying in Character used actors as one example, arguing that most actors’ worst movies are when they were (as the Hollywood expression goes) playing against type, such as John Wayne as a Roman centurion, Sylvester Stallone in Stop! Or My Mom Will Shoot, or Macaulay Culkin playing a psychopathic murderer.  While defying type entirely, or successfully playing against it, is undoubtedly a great accomplishment for an actor, most audiences don’t like it.

We want John Wayne as the tough lawman, Sylvester Stallone as Rocky Balboa, and the Home Alone kid as the Home Alone kid.   We want actors playing in type, not against it.

It’s a straight conflict of interest between the actor/product and the audience/consumer.  Hugh Grant wants to show the world that he can play a role other than the romantic Englishman.  However, just as we want our coffees customized at Starbucks and the restrooms clean at McDonald’s, we want Hugh Grant to be a romantic Englishman.  We don’t care if Hugh Grant is bored of being Hugh Grant.  That’s his problem.

Musicians have the same challenge.  They get tired of playing the same old songs and want to play their newer material, but the fans want to hear the classics [2].  James Taylor, ever humorous, put this well in discussing his hit cover of You’ve Got a Friend.

Taylor described the night he first heard songwriter Carole King perform the song. Taylor got so excited that, he said, “I literally ran to get my guitar and try to learn how to play it. Of course, I didn’t realize then I’d be playing it every night for the rest of my life.”

The other example I remember from the video was a discussion of Jack Daniels, who’s been credited with creating one of the longest-running advertising campaigns in history.  Here are two of their ads from the 1980s.

That’s branding.  It starts with the product and the packaging.  But it’s also as much about who you are as how you talk.  (By the way, isn’t that copywriting delightful?)

While storytelling is all the current marketing rage, and while these ads certainly tell stories, staying in character goes beyond the telling of individual stories to how you link numerous brand-building stories together over time.

Really, it’s about one thing:  consistency.

  • Defining who you are (your essence) and how you talk (your voice)
  • Consistently communicating your essence in your voice — always, never playing against type
  • Sticking with that come hell, high water, or — much more dangerously — a new CMO

It’s about you being you.  Or, for that matter, Hugh being Hugh.  And it’s why:

In the end, it’s about defining who you are, communicating it, and sticking with it.  That’s staying in character.  And it’s critical to any branding effort.

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Notes

[1] Yesterday’s guess was Hal Riney, but I don’t think it was him.  The voice was too warm and not nasal enough.

[2] Even the Grateful Dead, despite their improvisational style, deep repertoire, and ever-changing setlists, fell subtly victim to the “what we want to play” vs. “what they want to hear” phenomenon.