Category Archives: demandgen

Fortella Webinar: Crisis Mode — I Need More Pipeline Now!

Please join me and Fortella founder Rahul Sachdev for a webinar this Thursday (6/24/21) at 10am Pacific entitled Crisis Mode — I Need More Pipeline Now!

Fortella, which I’ve served as an advisor over the past year or so, makes a revenue intelligence platform.  The company recently published an interesting survey report entitled The State of B2B Marketing:  What Sets the Best Marketers Apart?  Rahul is super passionate about marketing accountability for revenue and the use of AI and advanced analytics in so doing, which is what drew me to want to work with him the first place.  He’s also an avid Kellblog reader, to the point where he often reminds me of things I’ve said but forgotten!

In this webinar we’ll drive a discussion primarily related to two Kellblog posts:

Among other things, I expect we’ll discuss:

  • That pipeline isn’t a monolith and that we need to look inside the pipeline to see things by opportunity type (e.g., new vs. expansion), customer type (e.g., size segment, industry segment) and by source (e.g., inbound vs. partners).  We also need to remember that certain figures we burn into our heads (e.g., sales cycle length) are merely the averages of a distribution and not impenetrable hard walls.
  • By decomposing pipeline we can identity that some types close faster (and/or at a higher conversion rate) than others, and ergo focus on those types when we are in a pinch.
  • How to think about pipeline coverage ratios, including to-go coverage, the target coverage ratio, and remembering to look not just at ARR dollar coverage but opportunities/rep.
  • The types of campaigns one can and should run when you are in a pipeline pinch
  • How we can avoid getting into pipeline pinches through planning (e.g., an inverted funnel model) and forecasting (e.g., next quarter pipeline).

I hope to see you there.  Register here.

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.

Marketing Targeting: It’s Not Just Where You Fish, It’s What You Put on the Hook

Back in the day I was taught that marketers do three things, memorized via the acronym STP:  segment, target, position.

  • Divide the audience into different segments.  For example, dividing consumers by demographics or dividing businesses by size or industry.
  • Select the segments that the company wishes to target for its marketing.  For example, choosing small and medium businesses (SMB) as your target segment.
  • Position the product in the mind of the consumer, ideally in a unique way, providing differentiation and/or benefit [1].  For example, positioning your offering for the SMB segment as easy to deploy and inexpensive to own.

I’ve always thought of targeting as the answer to the question, “what list do I want to buy?”  Do I want buy a list of marketing directors at SMBs or a list of chief data officers (CDOs) at Fortune 1000 companies?

The list-buying metaphor extends nicely to events (what shows do these people attend), PR (what publications do they read), AR (to which influencers do they listen), some forms of digital advertising (e.g., LinkedIn where you have considerable targeting control), if not Google (where you don’t [2]).

For many people, that’s where the targeting discussion ends.  When most people think of targeting they think of where on the lake they want to fish.

While an angler would never forget this, marketers too often miss that what you put on the hook matters, too.  Fishing in the same part of the lake, an angler might put on crayfish for largemouth bass, worms for rainbow trout, or stinkbait for catfish.

It’s not just about who you’re speaking to; it’s about what you tell them — the bait, if you will, that you put on the hook.

Perhaps this is too metaphorical, so let’s take an example — imagine we sell financial planning and budgeting software to businesses and our target segment is small businesses between $0M to $50M in revenue.  Via some marketing channels we can communicate only to people in this segment, but through a lot of other important channels (e.g., Google Ads, SEO, content marketing), we cannot.  So we need to rely not only on our targeting, but our message, to control who we bring into the lead funnel.

Consider these two messages:

  • Plan faster and more efficiently with OurTool
  • End the misery and mistakes of planning on Excel

The first message pitches a generic benefit of a planning system and is likely to attract many different types of fish.  The second message specifically addresses the pains of planning on Excel.  Who plans on Excel?  Well, smaller businesses primarily [3].  So the message itself helps us filter for the kind of companies we want to attract.

Now, let’s pretend we’re targeting large enterprises, instead.  Consider these two messages.

  • End the misery and mistakes of planning on Excel
  • Integrate your sales and financial planning

The first message, as discussed above, is going to catch a lot of small fish.  The second message is about a problem that only larger organizations face — small companies are just trying to get a budget done, whereas larger ones are trying to get a more holistic view.  The second message far better attracts the enterprise target that you want.  As would, for example, a message about the pain and expense of budgeting on Hyperion.

I’ll close in noting that marketers who measure themselves by the number of fish they catch [4] — as opposed to the conversion of those fish into customers — will often resist the more focused message because you won’t set attendance records with the more selective bait.  So, as you perform your targeting, always remember three things:

  1. It’s about where you put the boat
  2. It’s also about the bait you put on the hook
  3. It’s not about the number of fish you catch, but the number of the right fish that you catch.

# # #

Notes

[1] The decision to emphasize differentiation or benefit is covered in The Two Archetypal Marketing Messages:  “Bags Fly Free” and “Soup is Good Food.”

[2] In a B2B sense, at least.

[3] Amazingly, a lot of large and very large businesses also plan on Excel, but let’s not confuse the exception for the rule or the point of the example — different messages attract different buyers.

[4] Either literally by putting KPIs on high-funnel metrics such as MQLs or, more subtly and more dangerously, by getting too much inner joy from high-funnel metrics (“look how many people came to our webinar!”)

Should Your SDRs Look for Projects or Pain?

There’s a common debate out there, it goes something like this:

“Our sales development representatives (SDRs) need to look for pain: finding business owners with a problem and the ability to get budget to go fix it.”

Versus:

“No, our SDRs need to look for projects: finding budgeted projects where our software is needed, and ideally an evaluation in the midst of being set up.”

Who’s right?

As once was once taught to me, the answer to every marketing question is “it depends” and the genius is knowing “on what.”  This question is no exception.  The answer is:  it depends.  And on:

  • Whether you’re in a hot or cold market.
  • Whether your SDR is working an inbound or outbound motion

I first encountered this problem decades ago rolling out Solution Selling (from which sprung the more modern Customer-Centric Selling).  Solution Selling was both visionary and controversial.  Visionary in that it forced sales to get beyond selling product (i.e., selling features, feeds, and speeds) instead focusing on the benefits of what the product did for the customer.  Controversial in that it uprooted traditional sales thinking — finding an existing evaluation was bad, argued Bosworth, because it meant that someone else had already created the customer’s vision for a solution and thus the buying agenda would be biased in their favor.

While I think Bosworth made an interesting point about the potential for wired evaluation processes and requests for proposal (RFPs), I never took him literally.  Then I met what I could only describe as “fundamentalist solution seller” in working on the rollout.

“OK, we we’re working on lead scoring, and here’s what we’re going to do:  10 points for target industry, 10 points for VP title or above, 10 points for business pain, -10 points for existing evaluation, and -10 points for assigned budget.”

Wut?

I’d read the book so I knew what Bosworth said, but, but he was just making a point, right?  We weren’t actually going to bury existing evaluations in the lead pile, were we?  All because the customer knew they wanted to buy in our category and had the audacity to start an evaluation process and assign budget before talking to us?

That would be like living in the Upside Down.  We couldn’t possibly be serious?  Such is the depth of religion often associated with the rollout of a new sales methodology.

Then I remembered the subtitle of the book (which everyone seems to forget).

“Creating buyers in difficult selling markets.”  This was not a book written for sellers in Geoffrey Moore’s tornado, it was book for written for those in difficult markets, tough markets, markets without a lot of prospects, i.e., cold markets.  In a cold market, no one’s out shopping so you have no choice but find potential buyers in latent pain, inform them a solution exists, and try to sell it to them.

Example:  baldness remedies.  Sure, I’d rather not be bald, but I’m not out shopping for solutions because I don’t think they exist.  This is what solution sellers call latent pain.  Thus, if you’re going to sell me a baldness remedy, you’re going need to find me, get my attention, remind me that I don’t like being bald, then — and this is really hard part — convince me that you have a solution that isn’t snake oil.  Such is life in cold markets.  Go look for pain because if you look for buyers you aren’t going to find many.

However, in hot markets there are plenty of buyers, the market has already convinced buyers they need to buy a product, so the question sellers should focus on is not “why buy one” but instead, “why buy mine.”

I’m always amazed that people don’t first do this high-level situation assessment before deciding on sales and marketing messaging, process, and methodology.  I know it’s not always black & white, so the real question is:  to what extent are our buyers already shopping vs. need to be informed about potential benefits before considering buying?  But it’s hard to devise any strategy without having an answer to it.

So, back to SDRs.

Let’s quickly talk about motion.  While SDR teams may be structured in many ways (e.g., inbound, outbound, hybrid), regardless of team structure there are two fundamentally different SDR motions.

  • Inbound.  Following-up with people who have “raised their hand” and shown interest in the company and its offerings.  Inbound is largely a filtering and qualification exercise.
  • Outbound.  Targeting accounts (and people within them) to try and mutate them into someone interested in the company and its offerings.  In other words, stalking:  we’re your destiny (i.e., you need to be our customer) and you just haven’t figured it out, yet.

In hot markets, you can probably fully feed your salesforce with inbound.  That said, many would argue that, particularly as you scale, you need to be more strategic and start picking your customers by complementing inbound with a combination of named-account selling, account-based marketing, and outbound SDR motion.

In cold markets, the proverbial phone never rings.  You have no choice but to target buyers with power, target pains, and convince them your company can solve them.

Peak hype-cycle markets can be confusing because there’s plenty of inbound interest, but few inbound buyers (i.e., lots of tire-kickers) — so they’re actually cold markets disguised as hot ones.

Let’s finally answer the question:

  • SDRs in hot markets should look for projects.
  • SDRs in cold markets should look for pain.
  • SDRs in hot markets at companies complementing inbound with target-account selling should look for pain.

 

Why Every Startup Needs an Inverted Demand Generation Funnel, Part III

In part I of this three-part series I introduced the idea of an inverted funnel whereby marketing can derive a required demand generation budget using the sales target and historical conversion rates.  In order to focus on the funnel itself, I made the simplifying assumption that the company’s new ARR target was constant each quarter. 

In part II, I made things more realistic both by quarterizing the model (with increasing quarterly targets) and accounting for the phase lag between opportunity generation and closing that’s more commonly known as “the sales cycle.”  We modeled that phase lag using the average sales cycle length.  For example, if your average sales cycle is 90 days, then opportunities generated in 1Q19 will be modeled  as closing in 2Q19 [1].

There are two things I dislike about this approach:

  • Using the average sales cycle loses information contained in the underlying distribution.  While deals on average may close in 90 days, some deals close in 30 while others may close in 180. 
  • Focusing only on the average often leads marketing to a sense of helplessness. I can’t count the number of times I have heard, “well, it’s week 2 and the pipeline’s light but with a 90-day sales cycle there is nothing we can do to help.”  That’s wrong.  Some deals close more quickly than others (e.g., upsell) so what can we do to find more of them, fast [2].

As a reminder, time-based close rates come from doing a cohort analysis where we take opportunities created in a given quarter and then track not only what percentage of them eventually close, but when they close, by quarter after their creation. 

This allows us to calculate average close rates for opportunities in different periods (e.g., in-quarter, in 2 quarters, or cumulative within 3 quarters) as well an overall (in this case, six-quarter) close rate, i.e., the cumulative sum.  In this example, you can see an overall close rate of 18.7% meaning that, on average, within 6 quarters we close 18.7% of the opportunities that sales accepts.  This is well within what I consider the standard range of 15 to 22%.

Previously, I argued this technique can be quite useful for forecasting; it can also be quite useful in planning.  At the risk of over-engineering, let’s use the concept of time-based close rates  to build an inverted funnel for our 2020 marketing demand generation plan.

To walk through the model, we start with our sales targets and average sales price (ASP) assumptions in order to calculate how many closed opportunities we will need per quarter.  We then drop to the opportunity sourcing section where we use historical opportunity generation and historical time-based close rates to estimate how many closed opportunities we can expect from the existing (and aging) pipeline that we have already generated.  Then we can plug our opportunity generation targets from our demand generation plan into the model (i.e., the orange cells).  The model then calculates a surplus or (gap) between the number of closed opportunities we need and those the model predicts. 

I didn’t do it in the spreadsheet, but to turn that opportunity creation gap into ARR dollars just multiply by the ASP.  For example, in 2Q20 this model says we are 1.1 opportunities short, and thus we’d forecast coming in $137.5K (1.1 * $125K) short of the new ARR plan number.  This helps you figure out if you have the right opportunity generation plan, not just overall, but with respect to timing and historical close rates.

When you discover a gap there are lots of ways to fix it.  For example, in the above model, while we are generating enough opportunities in the early part of the year to largely achieve those targets, we are not generating enough opportunities to support the big uptick in 4Q20.  The model shows us coming in 10.8 opportunities short in 4Q20 – i.e., anticipating a new ARR shortfall of more than $1.3M.  That’s not good enough.  In order to achieve the 4Q20 target we are going to need to generate more opportunities earlier in the year.

I played with the drivers above to do just that, generating an extra 275 opportunities across the year generating surpluses in 1Q20 and 3Q20 that more than offset the small gaps in 2Q20 and 4Q20.  If everything happened exactly according to the model we’d get ahead of plan and 1Q20 and 3Q20 and then fall back to it in 2Q20 and 4Q20 though, in reality, the company would likely backlog deals in some way [3] if it found itself ahead of plan nearing the end of one quarter with a slightly light pipeline the next. 

In concluding this three-part series, I should be clear that while I often refer to “the funnel” as if it’s the only one in the company, most companies don’t have just one inverted funnel.   The VP of Americas marketing will be building and managing one funnel that may look quite different from the VP of EMEA marketing.  Within the Americas, the VP may need to break sales into two funnels:  one for inside/corporate sales (with faster cycles and smaller ASPs) and one for field sales with slower sales cycles, higher ASPS, and often higher close rates.  In large companies, General Managers of product lines (e.g., the Service Cloud GM at Salesforce) will need to manage their own product-specific inverted funnel that cuts across geographies and channels. There’s a funnel for every key sales target in a company and they need to manage them all.

You can download the spreadsheet used in this post, here.

Notes

[1] Most would argue there are two phase lags: the one from new lead to opportunity and the one from opportunity (SQL) creation to close. The latter is the sales cycle.

[2] As another example, inside sales deals tend to close faster than field sales deals.

[3] Doing this could range from taking (e.g., co-signing) the deal one day late to, if policy allows, refusing to accept the order to, if policy enables, taking payment terms that require pushing the deal one quarter back.  The only thing you don’t want to is to have the customer fail to sign the contract because you never know if your sponsor quits (or gets fired) on the first day of the next quarter.  If a deal is on the table, take it.  Work with sales and finance management to figure out how to book it.