Category Archives: SaaS

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

Does my company spend too much on marketing? Too little? How I do know? What is the right level of marketing spend at an enterprise software startup? I get asked these questions all the time by startup CEOs, CMOs, marketing VPs, and marketing directors.

You can turn to financial benchmarks, like the KeyBanc Annual SaaS Survey for some great high-level answers. You can subscribe to SiriusDecisions for best practices and survey data. Or you can buy detailed benchmark data [1] from OPEXEngine. These are all great sources and I recommend them heartily to anyone who can afford them.

But, in addition to sometimes being too high-level [2], there is one key problem with all these forms of benchmark data: they’re not about you. They’re not based on your operating history. While I certainly recommend that executives know their relevant financial benchmarks, there’s a difference between knowing what’s typical for the industry and what’s typical for you.

So, if you want to know if your company is spending enough on marketing [3], the first thing you should do is to make an inverted demand generation (aka, demandgen) funnel to figure out if you’re spending enough on demandgen. It’s quite simple and I’m frankly surprised how few folks take the time to do it.

Here’s an inverted demandgen funnel in its simplest form:

Inverted demandgen funnel

Let’s walk through the model. Note that all orange cells are drivers (inputs) and the white cells are calculations (outputs). This model assumes a steady-state situation [4] where the company’s new ARR target is $2,000,000 each quarter. From there, we simply walk up the funnel using historical deal sizes and conversion rates [5].

  • With an average sales price (ASP) of $75,000, the company needs to close 27 opportunities each quarter.
  • With a 20% sales qualified lead (SQL) to close rate we will need 133 SQLs per quarter.
  • If marketing is responsible for generating 80% of the sales pipeline, then marketing will need to generate 107 of those SQLs.
  • If our sales development representatives (SDRs) can output 2.5 opportunities per week then we will need 5 SDRs (rounding up).
  • With an 80% SAL to SQL conversion rate we will need 133 SALs per quarter.
  • With a 10% MQL to SAL conversion rate we will need 1,333 MQLs per quarter.
  • With a cost of $250 per MQL, we will need a demandgen budget [6] of $333,333 per quarter.

The world’s simplest way to calculate the overall marketing budget at this point would be to annualize demandgen to $1.3M and then double it, assuming the traditional 50/50 people/programs ratio [7].

Not accounting for phase lag or growth (which will be the subjects of part II and part III of this post), let’s improve our inverted funnel by adding benchmark and historical data.

Let’s look at what’s changed. I’ve added two columns, one with 2019 actuals and one with benchmark data from our favorite source. I’ve left the $2M target in both columns because I want to compare funnels to see what it would take to generate $2M using either last year’s or our benchmark’s conversion rates. Because I didn’t want to change the orange indicators (of driver cells) in the left column, when we have deviations from the benchmark I color-coded the benchmark column instead. While our projected 20% SQL-to-close rate is an improvement from the 18% rate in 2019, we are still well below the benchmark figure of 25% — hence I coded the benchmark red to indicate a problem in this row. Our 10% MQL-to-SQL conversion rate in the 2020 budget is a little below the benchmark figure of 12%, so I coded it yellow. Our $250 cost/MQL is well below the benchmark figure of $325 so I coded it green.

Finally, I added a row to show the relative efficiency improvement of the proposed 2020 budget compared to last year’s actuals and the benchmark. This is critical — this is the proof that marketing is raising the bar on itself and committed to efficiency improvement in the coming year. While our proposed funnel is overall 13% more efficient than the 2019 funnel, we still have work to do over the next few years because we are 23% less efficient than we would be if we were at the benchmark on all rates.

However, because we can’t count on fixing everything at once, we are taking a conservative approach where we show material improvement over last year’s actuals, but not overnight convergence to the benchmark — which could take us from kaizen-land to fantasy-land and result in a critical pipeline shortage downstream.

Moreover because this approach shows not only a 13% overall efficiency improvement but precisely where you expect it to come from, the CEO can challenge sales and marketing leadership:

  • Why are we expecting to increase our ASP by $5K to $75K?
  • Why do you think we can improve the SQL-to-close rate from 18% to 20% — and what you are doing to drive that improvement? [8]
  • What are we doing to improve the MQL-to-SAL conversion rate?
  • How are we going to improve our already excellent cost per MQL by $25?

In parts II and III of this post, we’ll discuss two ways of modeling phase-lag, modeling growth, and the separation of the new business and upsell funnels.

You can download my spreadsheet for this post, here.

Notes

[1] For marketing or virtually anything else.

[2] i.e., looking at either S&M aggregated or even marketing overall.

[3] The other two pillars of marketing are product marketing and communications. The high-level benchmarks can help you analyze spend on these two areas by subtracting your calculated demandgen budget from the total marketing budget suggested by a benchmark to see “what’s left” for the other two pillars. Caution: sometimes that result is negative!

[4] The astute reader will instantly see two problems: (a) phase-lag introduced by both the lead maturation (name to MQL) and sales (SQL to close) cycles and (b) growth. That is, in a normal high-growth startup, you need enough leads not to generate this quarter’s new ARR target but the target 3-4 quarters out, which is likely to be significantly larger. Assuming a steady-state situation gets rid of both these problems and simplifies the model. See part II and part III of this post for how I like to manage that added real-world complexity.

[5] Hint: if you’re not tracking these rates, the first good thing about this model is that it will force you to do so.

[6] When I say demandgen budget, I mean money spent on generating leads through marketing campaigns. Sometimes that very directly (e.g., adwords). Other times it’s a bit indirectly (e.g., an SEO program). I do not include demandgen staff because I am trying to calculate the marginal cost of generating an extra MQL. That is, I’m not trying to calculate what the company spends, in total, on demandgen activities (which would include salary, benefits, stock-based comp, etc. for demandgen staff) but instead the marketing programs cost to generate a lead (e.g., in case we need to figure out how much to budget to generate 200 more of them).

[7] In an increasingly tech-heavy world where marketing needs to invest a lot in infrastructure as well, I have adapted the traditional 50/50 people/programs rule to a more modern 45/45/10 people/programs/infrastructure rule, or even an infrastructure-heavy split of 40/40/20.

[8] Better closing tools, an ROI calculator, or a new sales training program could all be valid explanations for assuming an improved close rate.

Number 7 on the All-Time Top SaaStr Podcasts: On the Importance of LTV/CAC

Just a quick post to say I’m honored to have made number seven on the countdown of the top ten most downloaded podcasts of all time on the SaaStr Podcast.

The podcast in question is an interview performed by Harry Stebbings of The Twenty Minute VC where we sat down to talk about the importance of the lifetime value to customer acquisition cost ratio (LTV/CAC) and why, if you could only know one SaaS metric about a company, that LTV/CAC would be it.

Of course with Harry it’s easy to end up in a wide-ranging conversation, as we did, and we thus discussed many other fun topics including:

  • How I got into enterprise software and SaaS.
  • The biggest challenge as a leader in a high-growth company (hanging on).
  • Why, for a public SaaS company, I’d probably take billings growth as the single metric, because LTV/CAC isn’t available.
  • LTV/CAC and the idea that it’s a powerful (if compound) metric that weights what you pay for something vs. what’s it worth.
  • Which churn metric to use as the basis for calculating LTV.
  • Upsell and how to design your packaging to enable both incremental upsell and major cross-sell.
  • Pricing and how to ensure your pricing is linked to at least one metric that always increases.
  • Bookings and the perils of TCV in SaaS companies, including my favorite self-quote from the podcast: “beware of Greeks bearing gifts as you would beware SaaS companies talking TCV.”
  • Multi-year deals and to what extent they should be prepaid.
  • How once, at Business Objects, we once sold a customer more licenses than they had employees (on the broader topic of vendor/customer interest alignment).
  • How sales and customer success should work together on renewals and upsells — and importance of putting farmers vs. farmers and hunters vs. hunters when it comes to competition.
  • How you can’t analyze churn by analyzing churn — i.e., gathering a list of churned customers and looking for commonalities.
  • The 90 day rule when it comes to new managers.

I hope you enjoy listening to it if you haven’t already. And for those who have, thanks for helping me make the top 10 list!

Do We Have Enough Pipeline? The One Simple Metric Many Folks Forget.

Pipeline is a frequently scrutinized SaaS company metric because it’s one of relatively few leading indicators in a SaaS business — i.e., indicators that don’t just tell us about the past but that help inform us about the future, providing important clues to our anticipated performance this quarter, next quarter, and the one after that.

Thus, pipeline gets examined a lot.  Boards and investors love to look at:

  • Aggregate pipeline for the year, and how it’s changing [1]
  • Pipeline coverage for the quarter and whether a company has the magical 3x coverage ratio that most require [2]
  • Pipeline with and without the high funnel (i.e., pipeline excluding stage 1 and stage 2 opportunities) [3]
  • Pipeline scrubbing and the process a company uses to keep its pipeline from getting inflated full of junk including, among other things, rolling hairballs.
  • Expected values of the pipeline that create triangulation forecasts, such as stage-weighted expected value or forecast-category-weighted expected value.

But how much pipeline is enough?

“I’ve got too much pipeline, I wish the company would stop sending so many opportunities my way”  — Things I Have Never Heard a Salesperson Say.

Some try to focus on building an annual pipeline.  I think that’s misguided.  Don’t focus on the long-term and hope the short-term takes care of itself; focus consistently on the short-term and long-term will automatically take care of itself.  I made this somewhat “surprised that it’s seen as contrarian” argument in I’ve Got a Crazy Idea:  How About We Focus on Next-Quarter’s Pipeline?

But somehow, amidst all the frenzy a very simple concept gets lost.  How many opportunities can a salesperson realistically handle at one time? 

Clearly, we want to avoid under-utilizing salespeople — the case when they are carrying too few opportunities.  But we also want to avoid them carrying too many — opportunities will fall through the cracks, prospect voice mails will go unreturned, and presentations and demos will either be hastily assembled or the team will request extensions to deadlines [4].

So what’s the magic metric to inform you if you have too little, too much, or just the right amount of pipeline?  Opportunities/salesrep — measured both this-quarter and for all-quarters.

What numbers define an acceptable range?

My first answer is to ask salesreps and sales managers before they know what you’re up to.  “Hey Sarah, out of curiosity, how many current-quarter opportunities do you think a salesrep can actually handle?”  Poll a bunch of your team and see what you get.

Next, here are some rough ranges that I’ve seen [5]:

  • Enterprise reps:  6 to 8 this-quarter and 12 to 15 all-quarters opportunities
  • Corporate reps:  10 to 12 this-quarter and 15 to 20 all-quarters opportunities

I’ve been in meetings where the CRO says “we have enough pipeline” only to discover that they are carrying only 2.5 current-quarter opportunities per salesrep [6].  I then ask two questions:  (1) what’s your close rate and (2) what’s your average sales price (ASP)?  If the CRO says 40% and $125K, I then conclude the average salesrep will win one (0.4 * 2.5 = 1), $125K deal in the quarter, about half a typical quota.  I then ask:  what do the salesreps carrying 2.5 current-quarter opportunities actually do all day?  You told me they could carry 8 opportunities and they’re carrying about a quarter of that?  Silence usually follows.

Conversely, I’ve been in meetings where the average enterprise salesrep is carrying close to 30 large, complex opportunities.  I think:  there’s no way the salesreps are adequately servicing all those deals.  In such situations, I have had SDRs crying in my office saying a prospect they handed off to sales weeks ago called them back, furious about the poor service they were getting [7].  I’ve had customers call me saying their salesrep canceled a live demo on five minutes’ notice via a chickenshit voicemail to their desk line after they’d assembled a room full of VIPs to see it [8].  Bad things happen when your salesreps are carrying too many opportunities.

If you’re in this situation, hire more reps.  Give deals to partners.  Move deals from enterprise to corporate sales.  But don’t let opportunities that cost the company between $2,000 and $8,000 to create just rot on the table.  As I reminded salesreps when I was a CEO:  they’re not your opportunities, they’re my opportunities — I paid for them.

Hopefully, I’ve made the case that going forward, while you should keep tracking pipeline on an ARR basis and looking at ARR conversion rates, you should add opportunity count and opportunity count / salesrep to your reports on the current-quarter and the all-quarters pipeline.  It’s the easiest and most intuitive way to understand the amount of your pipeline relative to your ability to process it.

# # #

Notes

[1] With an eye to two rules of thumb:  [a] that annual starting pipeline often approximate’s this year’s annual sales and [b] that the YoY growth rate in the size of the pipeline predicts YoY growth rate in sales.

[2] Pipeline coverage = pipeline / plan.  So if you have 300 units of pipeline and a new ARR plan of 100 units, then you have 3.0x pipeline coverage.

[3] Though there’s a better way to solve this problem — rather than excluding early-stage opportunities that have been created with a placeholder value, simply create new opportunities with value of $0.  That way, there’s nothing to exclude and it creates a best-practice (at most companies) that sales can’t change that $0 to a value without socializing the value with the customer first.

[4] The High Crime of a company slowing down its own sales cycles!  Never forget the sales adage:  “time kills all deals.”

[5] You can do a rough check on these numbers using close rates and ASPs.  If your enterprise quota is $300K/quarter, your ASP $100K, and your close rate 33%, a salesrep will need 9 current-quarter opportunities to make their number.

[6] The anemic pipeline hidden, on an ARR basis, by (unrealistically) large deal sizes.

[7] And they actually first went to HR seeking advice about what to do, because they didn’t want “rat out” the offending salesrep.

[8] Invoking my foundational training in customer support, I listened actively, empathized, and offered to assign a new salesrep — the top rep in the company — to the account, if they’d give us one more chance.  That salesrep turned a deal that the soon-to-be-former salesrep was too busy to work on, into the deal of the quarter.

Kellblog's Greatest Hits 2016-2019 per the Appealie SaaS Awards

I’ll be speaking at the APPEALIE 2019 SaaS Conference and Awards in San Francisco on September 25th and I noticed that in their promotions the folks at APPEALIE had assembled their own Kellblog’s Greatest Hits album from 2016 to 2019, complete with its own cover art.
appealie
When I looked at the posts they picked, I thought they did a good job of identifying the best material, so I thought I’d share their list here.  They also called me “a GOAT software blogger” and after playing around with acronyms for about half an hour — maybe Groove, OpenView, AngelVC, Tunguz? — my younger son swung by and said, “they called you a GOAT?  Cool.  It means greatest of all time.”  Cool, indeed.  Thanks.
Here’s the APPEALIE Kellblog’s Greatest Hits 2016-2019 list:

 

New ARR and CAC in Price-Ramped vs. Auto-Expanding Deals

In this post we’re going to look at the management accounting side of multi-year SaaS deals that grow in value over time.  I’ve been asked about this a few times lately, less because people value my accounting knowledge [1] but rather because people are curious about the CAC impact of such deals and how to compensate sales on them.

Say you sign a three-year deal with a customer that ramps in payment structure:  year 1 costs $1M, year 2 costs $2M, and year 3 costs $3M.  Let’s say in this example the customer is getting the exact same value in all 3 years (e.g., the right for 1,000 people to use a SaaS service) – so the payment structure is purely financial in nature and not related to customer value.

Equal Value:  The Price-Ramped Deal
The question on my mind is how do I look at this from a new ARR bookings, ending ARR, CAC, and sales compensation perspective?

GAAP rules define precisely how to take this from a GAAP revenue perspective – and with the adoption of ASC 606 even those rules are changing.  Let’s take an example from this KPMG data sheet on ASC 606 and SaaS.

(Price-Ramped) Year 1 Year 2 Year 3
Payment structure $1M $2M $3M
GAAP revenue $1M $2M $3M
GAAP unbilled deferred revenue $5M $3M $0M
ASC 606 revenue $2M $2M $2M
ASC 606 unbilled accounts receivable $1M $1M $0M
ASC 606 revenue backlog $4M $2M $0M

When I look at this is I see:

  • GAAP is being conservative and saying “no cash, no revenue.” For an early stage startup with no history of actually making these deals come true, that is not a bad position.  I like the concept of GAAP unbilled deferred revenue, but I don’t actually know anyone who tracks it, let alone discloses it.  Folks might release backlog in some sort of unbilled total contract value (TCV) metric which I suspect is similar [2].
  • ASC 606 is being aggressive and mathematical – “hey, if it’s a 3-year, $6M deal, then that’s $2M/year, let’s just smooth it all out [3]”. While “unbilled A/R” strikes me as (another) oxymoron I see why they need it and I do like the idea of ASC 606 revenue backlog [4].  I think the ASC 606 approach makes a lot of sense for more mature companies, which have a history of making these deals work [5].

Now, from an internal, management accounting perspective, what do you want to do with this deal in terms of new ARR bookings, ending ARR balance, CAC ratio, and sales comp?  We could say:

  • It’s $2M in new ARR today
  • Ergo calculate this quarter’s CAC with it counted as $2M
  • Add $2M in ending ARR
  • Pay the salesrep on a $2M ARR deal – and let our intelligently designed compensation plan protect us in terms of the delayed cash collections [6] [6A]

And I’d be OK with that treatment.  Moreover, it jibes with my definition of ARR which is:

End-of-quarter ARR / 4 = next-quarter subscription revenue, if nothing changes [7]

That’s because ASC 606 also flattens out the uneven cash flows into a flat revenue stream.

Now, personally, I don’t want to be financing my customers when I’m at a high-burn startup, so I’m going to try and avoid deals like this.  But if I have to do one, and we’re a mature enough business to be quite sure that years 2 and 3 are really coming, then I’m OK to treat it this way.  If I’m not sure we’ll get paid in years 2 and 3 – say it’s for a brand-new product that has never been used at this scale – then I might revert to the more GAAP-oriented, 1-2-3 approach, effectively treating the deal not as a price ramp, but as an auto-expander.

Increasing Value:  The Auto-Expanding Deal
Let’s say we have a different use-case.  We sell a SaaS platform and year 1 will be exclusively focused on developing a custom SaaS app, we will roll it to 500 users day 1 of year 2, and we will roll it to 500 more users on day 1 of year 3.  Further assume that the customer gets the same value from each of these phases and each phase continues until the end of the contract [8].  Also assume the customer expects that going forward, they will be paying $3M/year plus annual inflation adjustments.

Oy veh.  Now it’s much harder.  The ramped shape of the curve is not about financing at all.  It’s about the value received by the customer and the ramped shape of the payments perfectly reflects the ramped shape of the value received.  Moreover, not all application development projects succeed and if they fall behind on building the customized application they will likely delay the planned roll-outs and try to delay the payments along with them.  Moreover, since we’re an early-stage startup we don’t have enough history to know if they’ll succeed at all.

This needs to be seen as an auto-expanding deal:  $1M of new-business ARR in year 1, $1M of pre-sold upsell ARR in year 2, and another $1M of pre-sold upsell ARR in year 3.

When you celebrate it at the company kickoff you can say the customer has made a $6M commitment (total contract value, or TCV [9]) to the company and when you tier your customers for customer support/success purposes you might do so by TCV as opposed to ARR [10].  When you talk to investors you can say that $1M of next year’s and $1M of the subsequent year’s upsell is already under contract, ergo increasing your confidence in your three-year plan.  Or you could roll it all together into a statement about backlog or RPO [11].  That part’s relatively easy.

The hard part is figuring out sales compensation and CAC.  While your rep will surely argue this is a $2M ARR deal (if not a $3M ARR deal) and that he/she should be paid accordingly, hopefully you have an ARR-driven (and not a total bookings-driven) compensation plan and we’ve already established that we can’t see this as $2M or $3M ARR deal.  Not yet, at least.

This deal is a layer cake:  it’s a three-year $1M ARR deal [12] that has a one-year-delayed, two-year $1M ARR deal layered atop it, and a two-year-delayed, one-year $1M ARR deal atop that.  And that, in my opinion, is how you should pay it out [13].  Think:  “hey, if you wanted to get paid on a three-year $3M ARR deal, then you should have brought me one of those [14].”

Finally, what to do about the CAC?  One might argue that the full cost of sale for the eventual $3M in ARR was born up-front.  Another might argue that, no, plenty of account management will be required to ensure we actually get the pre-sold upsell.  The easiest and most consistent thing to do is to treat the ARR as we mentioned (1+1+1) and calculate the CAC, as you normally would, using the ARR that we put in the pool.

If you do a lot of these deals, then you would see a high new-business CAC ratio that is easily explained by stellar net-dollar expansion rates (173% if these were all you did).  Think:  “yes, we spend a lot up-front to get a customer, but after we hook them, they triple by year three.”

Personally, I think any investor would quickly understand (and fall in love with) those numbers.  If you disagree, then you could always calculate some supplemental CAC ratio designed to better amortize the cost of sale across the total ARR [14].  Since you can’t have your cake and eat it too, this will make the initial CAC look better but your upsell CAC and net-dollar expansion rates worse.

As always, I think the right answer is to stick with the fundamental metrics and let them tell the story, rather than invent new metrics or worse yet, new definitions for standard metrics, which can sow the seeds of complexity and potential distrust.

# # #

Notes

For more information on ASC 606 adoption, I suggest this podcast and this web page which outlines the five core principles.

[1] I am not an accountant.  I’m a former CEO and strategic marketer who’s pretty good at finance.

[2] And which I like better as “unbilled deferred revenue” is somewhat oxymoronical to me.  (Deferred revenue is revenue that you’ve billed, but you have not yet earned.)

[3] I know in some cases, e.g., prepaid, flat multi-year deals, ASC 606 can actually decide there is a material financing event and kind of separate that from the core deal.  While pure in spirit, it strikes me as complex and the last time I looked closely at it, it actually inflated revenue as opposed to deflating it.

[4] Which I define as all the future revenue over time if every contract played out until its end.

[5] Ergo, you have high empirical confidence that you are going to get all the revenue in the contract over time.

[6] Good comp plans pay only a portion of large commissions on receipt of the order and defer the balance until the collection of cash.  If you call this a $2M ARR deal, you do the comp math as if it’s $2M, but pay out the cash as dictated by the terms in your comp plan.  (That is, make it equivalent to a $2M ARR deal with crazy-delayed payment terms.)  You also retire $2M of quota, in terms of triggering accelerators and qualifying for club.

[6A] This then begs the question of how to comp the $1M in pre-sold upsell in Year 3.  As with any of the cases of pre-sold upsell in this post, my inclination is to pay the rep on it when we get the cash but not on the terms/rates of the Year 1 comp plan, but to “build it in” into their comp plan in year 3, either directly into the structure (which I don’t like because I want reps primarily focused on new ARR) or as a bonus on top of a normal OTE.  You get a reward for pre-sold upsell, but you need to stay here to get it and you don’t year 1 comp plan rates.

[7] That is, if all your contracts are signed on the last day of the quarter, and you don’t sign any new ones, or churn any existing ones until the last day of the quarter, and no one does a mid-quarter expansion, and you don’t have to worry about any effects due to delayed start dates, then the ARR balance on the last day of the quarter / 4 = next quarter’s subscription revenue.

[8] Development is not “over” and that value released – assume they continue to fully exploit all the development environments as they continue to build out their app.

[9] Note that TCV can be seen as an “evil” metric in SaaS and rightfully so when you try to pretend that TCV is ARR (e.g., calling a three-year $100K deal “a $300K deal,” kind of implying the $300K is ARR when it’s not).  In this usage, where you’re trying to express total commitment made to the company to emphasize the importance of the customer, I think it’s fine to talk about TCV – particularly because it also indirectly highlights the built-in upsell yet to come.

[10] Or perhaps some intelligent mix thereof.  In this case, I’d want to weight towards TCV because if they are not successful in year 1, then I fail to collect 5/6th of the deal.  While I’d never tell an investor this was a $6M ARR deal (because it’s not true), I’d happily tell my Customer Success team that this a $6M TCV customer who we better take care of.  (And yes, you should probably give equal care to a $2M ARR customer who buys on one-year contracts – in reality, either way, they’d both end up “Tier 1” and that should be all that matters.)

[11] Or you could of the ASC 606 revenue backlog and/or Remaining Performance Obligation (RPO) – and frankly, I’d have trouble distinguishing between the two at this point.  I think RPO includes deferred revenue whereas ASC 606 revenue backlog doesn’t.

[12] In the event your compensation plan offers a kicker for multi-year contracts.

[13] And while you should factor in the pre-committed upsell in setting the reps targets in years 2 and 3, you shouldn’t go so far as to give them a normal upsell target with the committed upsell atop it.  There is surely middle ground to be had.  My inclination is to give the rep a “normal” comp plan and build in collecting the $1M as a bonus on top — but, not of course at regular new ARR rates.  The alternative is to build (all or some of) it into the quota which will possibly demotivate the rep by raising targets and reducing rates, especially if you just pile $1M on top of a $1M quota.

[14] This ain’t one – e.g., it has $6M of TCV as opposed to $9M.

Ten Ways to Get the Most out of Conferences

I can’t tell you the number of times, as we were tearing down our booth after having had an epic show, that we overheard the guy next door calling back to corporate saying that the show was a “total waste of time” and that the company shouldn’t do it again next year.  Of course, he didn’t say that he:

  • Staffed the booth only during scheduled breaks and went into the hallway to take calls at other times.
  • Sat inside the booth, safely protected from conference attendees by a desk.
  • Spent most of his time looking down at his phone, even during the breaks when attendees were out and about.
  • Didn’t use his pass to attend a single session.
  • Measured the show solely by qualified leads for his territory, discounting company visibility and leads for other territories to zero.

slack boothDoes this actually happen, you think?  Absolutely

All the time.  (And it makes you think twice when you’re on the other end of that phone call – was the show bad or did we execute it poorly?) 

I’m a huge believer in live events and an even bigger believer that you get back what you put into them.  The difference between a great show and a bad show is often, in a word, execution.  In this post, I’ll offer up 10 tips to ensure you get the best out of the conferences you attend.

Ten Ways to Get the Most out of Conferences and Tradeshows

1. Send the right people.  Send folks who can answer questions at the audience’s level or one level above.  Send folks who are impressive.  Send folks who are either naturally extroverts or who can “game face” it for the duration of the show.  Send folks who want to be there either because they’re true believers who want to evangelize the product or because they believe in karma [1].  Send senior people (e.g., founders, C-level) [2] so they can both continue to refine the message and interact with potential customers discussing it.

2. Speak.  Build your baseline credibility in the space by blogging and speaking at lesser conferences.  Then, do your homework on the target event and what the organizers are looking for, and submit a great speaking proposal.  Then push for it to be accepted.  Once it’s accepted, study the audience hard and then give the speech of your life to ensure you get invited back next year.  There’s nothing like being on the program (or possibly even a keynote) to build credibility for you and your company.  And the best part is that speaking a conference is, unlike most everything else, free.

3. If you can afford a booth/stand, get one.  Don’t get fancy here.  Get the cheapest one and then push hard for good placement [3].  While I included a picture of Slack’s Dreamforce booth, which is very fancy for most early-stage startup situations, imagine what Slack could have spent if they wanted to.  For Slack, at Dreamforce, that’s a pretty barebones booth.  (And that’s good — you’re going to get leads and engage with people in your market, not win a design competition.)

4. Stand in front of your booth, not in it.  Expand like an alfresco restaurant onto the sidewalk in spring.  This effectively doubles your booth space.

5. Think guerilla marketing.  What can make the biggest impact at the lowest cost?  I love stickers for this because a clever sticker can get attention and end up on the outside of someone’s laptop generating ongoing visibility.  At Host Analytics, we had great success with many stickers, including this one, which finance people (our audience) simply loved [4].

I LOVE EBITDA

While I love guerilla marketing, remember my definition:  things that get maximum impact at minimum cost.  Staging fake protests or flying airplanes with banners over the show may impress others in the industry, but they’re both expensive and I don’t think they impress customers who are primarily interested not in vendor politics, but in solving business problems.

6. Work the speakers.  Don’t just work the booth (during and outside of scheduled breaks), go to sessions.  Ask questions that highlight your issues (but not specifically your company).  Talk to speakers after their sessions to tee-up a subsequent follow-up call.  Talk to consultant speakers to try and build partnerships and/or fish to referrals.  Perhaps try to convince the speakers to include parts of your message into their speech [5].

7. Avoid “Free Beer Here” Stunts.  If you give away free beer in your booth you’ll get a huge list of leads from the show.  However, this is dumb marketing because you not only buy free beer for lots of unqualified people but worse yet generate a giant haystack of leads that you need to dig through to find the qualified ones — so you end up paying twice for your mistake.  While it’s tempting to want to leave the show with the most card swipes, always remember you’re there to generate visibility, have great conversations, and leave with the most qualified leads — not, not, not the longest list of names.

8. Host a Birds of a Feather (BoF).  Many conferences use BoFs (or equivalents) as a way for people with common interests to meet informally.  Set up via either an online or old-fashioned cork message board, anyone can organize a BoF by posting a note that says “Attention:  All People Interested in Deploying Kubernetes at Large Scale — Let’s Meet in Room 27 at 3PM.”  If your conference doesn’t have BoFs either ask the organizers to start them, or call a BoF anyway if they have any general messaging facility.

9. Everybody works. If you’re big enough to have an events person or contractor, make sure you define their role properly.  They don’t just set up the booth and go back to their room all day.  Everybody works.  If your events person self-limits him/herself by saying “I don’t do content,” then I’d suggest finding another events person.

10.  No whining.  Whenever two anglers pass along a river and one says “how’s the fishing?” the universal response is “good.”  Not so good that they’re going to ask where you’ve been fishing, and not so bad that they’re going to ask what you’ve been using.  Just good.  Be the same way with conferences.  If asked, how it’s going, say “good.”  Ban all discussion and/or whining about the conference until after the conference.  If it’s not going well, whining about isn’t going to help.  If it is going well, you should be out executing, not talking about how great the conference is.  From curtain-up until curtain-down all you should care about is execution.  Once the curtain’s down, then you can debrief — and do so more intelligently having complete information.

Notes

[1] In the sense that, “if I spend time developing leads that might land in other reps’ territories today, that what goes around comes around tomorrow.”

[2] In order to avoid title intimidation or questions about “why is your CEO working the booth” you can have a technical cofounder say “I’m one of the architects of the system” or your CEO say “I’m on the leadership team.”

[3] Build a relationship with the organizers.  Do favors for them and help them if they need you.  Politely ask if anyone has moved, upgraded, or canceled their space.

[4] Again note where execution matters — if the Host Analytics logo were much larger on the sticker, I doubt it would have been so successful.  It’s the sticker’s payload, so the logo has to be there.  Too small and it’s illegible, but too big and no one puts the sticker on their laptop because it feels like a vendor ad and not a clever sticker.

[5] Not in the sense of a free ad, but as genuine content.  Imagine you work at Splunk back in the day and a speaker just gave a talk on using log files for debugging.  Wouldn’t it be great if you could convince her next time to say, “and while there is clearly a lot of value in using log files for debugging, I should mention there is also a potential goldmine of information in log files for general analytics that basically no one is exploiting, and that certain startups, like Splunk, are starting to explore that new and exciting use case.”

Appearance on the Twenty Minute VC: Financing Thoughts, The Private Equity Sales Process, and More

Today famed venture capital podcaster and now venture capitalist at StrideVC, Harry Stebbings, released a new episode of the Twenty Minute VC podcast with me as his guest.  (iTunes version here.)

dk harry 500

Harry’s interview was broad-ranging, covering a number of topics including:

  • Financing lessons I’ve learned during prior bubble periods and, perhaps more importantly, bubble bursts.
  • The three basic types of exits available today:  strategic acquirer, old-school private equity (PE) squeeze play, and new-school PE growth and/or platform play.
  • A process view of exiting a company via a PE-led sales process, including discussion of the confidential information memorandum (CIM), indications of interest (IOIs), management meetings, overlaying strategic acquirers into the process, and the somewhat non-obvious final selection criteria.

The Soundcloud version, available via any browser is here.  The iTunes version is here.  Regardless of whether you are interested in the topics featured in this episode, I highly recommend Harry’s podcast and listen to it myself during my walking and/or driving time.

Oh, and if you like the content in this episode, don’t miss my first appearance on the show.