Even experienced leaders can easily forget that one voice shouldn’t drive change.

I try and write from recent inspiration and this post is far from an exception. Over the last few weeks, several of the CEOs we work with have all reinforced the problem of the lone voice driving change, which is a symptom of mismanagement of the SaaS feedback lifecycle. These are experienced business leaders who know better but can still get caught up in reacting to a single opinion. And it’s prevalent across disciplines too, with my recent experiences including sales, marketing, product road mapping, investor relations, and customer success.

SaaS companies that react to lone voices can have a hard time staying a course. They may also have fractured identities resulting from too many cooks in the kitchen. Mismanagement of the SaaS feedback lifecycle often manifests in product roadmaps that cater to a customer’s perspective rather than market need. This is probably most common in startups who listen to whale customers more than the market.

Listening and Acting Are Different

In SaaS, listening to feedback is critical to rapid iteration and growth. So we’re conditioned to listen to everything. We set up systems and processes to capture as much market feedback as we can — from prospects, from customers, from employees, from investors, from advisors, and so on. That’s perfect. We need to listen to everything. That’s easy.

But disseminating and acting on what we hear needs to be more discerning. This is where the SaaS feedback lifecycle gets dicey, even for seasoned pros. It can be hard not to act on a single voice, especially if we’re fragile on the topic, or nascent in our thinking. We get an input, perhaps from a very respected source, and we’re prone to execute against that perspective. But if it’s still only one, let’s think about how to validate that a bit more before acting.

Think Like a Journalist

The college for my advertising major at the University of Florida was journalism. So my core classes, before I got into my major, were journalism. Fact checking is the most basic of journalistic principles. If you can’t validate a fact with an additional source, it’s not a fact. We can apply that same standard to feedback we get.

If the lone voice is validated, by at least one, preferably two additional sources, then and only then is it worthy of consideration for action.

Even Surfacing the Lone Voice Can Be Disruptive

One thing it feels like we’re often reluctant to say — because it feels blasphemous — is that feedback can be just plain wrong. You can hear something from a lone voice and capture it. But if that voice automatically gets elevated in a staff@ message it gets credibility. If it’s wrong, it just planted a bad seed. So even widely disseminating all feedback can be disruptive. It’s about considering your audience. The leadership team should be able to handle everything. But to share everything with everyone in the company can be confusing and distracting. I’m all about transparency, but we need to strategically guide our organization through curation.

If you are in SaaS sales, you know a great demo can make or break your chances of winning the deal. But what you may not know is what actually makes a demo great. Most demos—yes most—are simply terrible. Which is a shame, because giving a killer demo just isn’t that hard.

Here’s a quick overview of how to give a great SaaS demo, and links to a few fantastic articles to help round things out.

Get a little introspective about the role of a demo in the sales cycle

A demo isn’t a perfunctory thing we do as a ‘check the box’ aspect of the sales cycle. A demo helps demonstrate how well you can help your customer solve a problem or attain a goal. A demo reinforces the value you can provide. A demo builds a relationship because it shows the sales rep has been listening—really listening—to the prospect.

I like to put the demo up on a pedestal so that we don’t go through the motions. To stimulate thought and discussion, here are some questions I always explore with my sales reps:

* What is the purpose of a demo?* When is the most opportune time to conduct a demo?* What makes a great demo?* What are the most important things to know prior to doing a demo?* What types of things should be avoided in a demo?

Win the deal with the demo

There is only one way to use the demo to win the deal. Know who you are demo’ing and what they care about, and stick to it.

Do not ramble, do not show every feature, do not do the same exact demo for every prospect. A demo should be a highly targeted experience where we show only what the prospect needs to know. When we do this well, it leads to natural curiosity on the part of the prospect and we can let the product ‘un-fold’ in front of them as they ask questions.

Before conducting a demo, you need to know what you are doing, why you are doing it and what’s going to matter most. Here is what I think you know, at a minimum, before ever conducting a demo (and if a sales engineer is conducting the demo, they need you to provide this information to them bneforehand):

* The 5-minute test. If the prospect only had 5 minutes, what would you have to show them in order to win the deal?* What’s the prospect’s specific need, pain, goal or aspiration?* Who will be on the call? What are their titles & roles in the organization?* Are they familiar with our product category?* What relevant tools are they currently using—including our competitors, our partners or adjacent software?* Do they have any specific technical or integration questions that have to get addressed right now?

If you do a 90-minute demo and you think you nailed it because the prospect ‘stayed engaged with you the whole time’, I can almost guarantee you didn’t nail it, you blew it. Long demos are boring. Long demos are overwhelming, Long demos aren’t targeted or specific.

Get very clear about what the prospect cares about and stick to that.

Don’t forget your demo basics

I hate to have to even write this part, because it’s just common sense. But I’ve sat on my share of demos where the sales rep forgot these simple steps. Before beginning a demo, please make sure you:

* Hide your dock* Hide notifications* Close all applications closed/minimized* Clean your browser, no open tabs other than what is needed for the demo* Have the right pages and applications pulled up and ready to go

Agile is great, but we need to continuously process and ingest what we learn. Here’s how.

Agile management across the majority of a SaaS organization provides the framework for rapid, innovation, iteration and improvement. Ultimately, the efficiency of that improvement comes down to how well we ingest and distribute what’s being learned — our SaaS learning loops.

I can’t tell you how many times we’ve seen concentrated pockets of institutional knowledge in growing SaaS companies. The result of that concentration is much more than dependency on those individuals. It directly impacts scalability. And, perhaps most significantly, it retards momentum and growth by trapping learning that would likely inform acceleration of ideas and people across the organization.

Institutional Knowledge Grubbing is Human Nature

Early employees of growing SaaS startups love their employee number. Part of that pride comes from knowing everything since the beginning. It’s a natural badge of honor, as well as a job security blanket. I’m not suggesting this is some intentional, malicious, diabolical plan to trap the knowledge. But I’ve seen the tendency a lot. And it usually hurts the organization.

SaaS organizations need to be built to naturally and continuously ingest and distribute what they learn.

The more widespread knowledge is, the more people can be inspired to draft their own ideas on top of it.

A Thin Layer of Process Atop Agile

Sprints and standups yield a lot of rapid learning. The challenge is that much of it slips through a sieve of standup conversation or ephemeral cards or tickets. Preservation isn’t a natural part of most processes.

But it doesn’t take much to change that pattern. The commitment to SaaS learning loops is really a cultural mandate to identify, ingest, and preserve what’s important. Not everything. Just what’s important. So on top of the cultural mandate from thetop, you need smart people who can make those decisions at the top of their learning funnel.

SaaS Learning Loops are a Management Thing

Hopefully, your smart people are in leadership roles. And hopefully, they’re standing in standups and retrospecting sprint boards. If those things are true, it’s incumbent on them to identify what’s important to preserve and annotate from your SaaS leanring loops. This is most notable in standups because so many valuable things can get lost in those brief updates — especially in sales and marketing. But once that muscle is habitually working, it’s thin and easy to capture the value.

But once they capture it, where does it go?

We like living, breathing wikis that the entire company knows to be the place for institutional knowledge. Each department can have its own section of the wiki that they curate on a periodic basis — start with quarterly curate-athons that the department collaborates on for an hour to review, cut, annotate and append recent learning. Then they can summarize their momentum makers to the organization in an all-hands format, email or slack channel that links back to the wiki. It’s not hard. It’s thin. And it works. Learning can easily become a rallying point and cultural lantern.

When looking at a problem, I have a simple framework for evaluating what’s wrong. Is it People, Product, Playbook or Process (or some combination thereof)? When the 4 P’s are all aligned and functioning well, great performance follows. And if we aren’t hitting numbers or executing well, then something within the 4 P’s isn’t right.

“Manage the cause, not the result.” ~W.E Deming

You may be familiar with the 4 P’s of Marketing. I’ve come to think of People, Product, Playbooks and Process as the 4 P’s of SaaS.

People

Often, we think we have the right people in the right seats in the bus. Until one day we realize we don’t. We’ve held on to people who didn’t grow with the organization. We hired poor culture fits. We hired based on anticipated needs versus actual needs. When you have a high-performing team, you just know it. So, if it doesn’t feel like you have a high-performing team, you probably don’t.

“…leaders of companies that go from good to great start not with “where” but with “who.” They start by getting the right people on the bus, the wrong people off the bus, and the right people in the right seats. And they stick with that discipline—first the people, then the direction—no matter how dire the circumstances.” ~Jim Collins

What are some other symptoms of not having the right people, in the right roles, doing the right things?

* Moving people around constantly trying to find the right spot for them.

* Managers who aren’t trained or equipped to manage.

* Lack of accountability and transparency.

* Unclear ‘chain of command’.

* Lack of trust, of each other and of the organization itself.

* Hodgepodge org chart, cobbled together over the years to patch over problems or shore up weaknesses.

* High turnover (both voluntary and involuntary).

* Lack of alignment and clarity around the mission, vision, strategic initiatives and goals.

Product

“You can always feel when product/market fit isn’t happening. The customers aren’t quite getting value out of the product, word of mouth isn’t spreading, usage isn’t growing that fast, press reviews are kind of ‘blah’, the sales cycle takes too long, and lots of deals never close. And you can always feel product/market fit when it’s happening. ~Marc Andreessen

A SaaS company is dead in the water without a great product, and product-market fit. This is fundamental and the symptoms are clear.

* Elusive product-market fit, always feeling like it’s right around the corner.

* Acquiring customers feels harder than it should.

* High customer churn rate.

* Low net retention.

* Quality issues—bugs, defects, confusing user experience.

* Management issues—lack of scalability, decaying code base, growing technical debt.

Playbook

A playbook says why and how we do things as an organization, a department, a team and an individual. Without playbooks for why and how we do things resources are wasted, efforts are often duplicated, and results are elusive (without clarity around why).

“…a playbook includes “process workflows, standard operating procedures, and cultural values that shape a consistent response—the play. A playbook reflects a plan; an approach or strategy defining predetermined responses worked out ahead of time.” ~Accenture

Here are some symptoms that a company is lacking effective playbooks for key functions:

* Takes too long to ramp new staff.

If your teams don’t understand and believe in your data, they won’t leap with you.

I’m a huge practitioner of data-driven SaaS management. I believe that almost everything in a SaaS business can and should be measured. But there are two important caveats to measurement that I’ve recently seen overlooked.

First, the data you use for KPIs or OKRs must be understood by your teams. And second, it must have perceived integrity. They have to know what the numbers mean and trust that they’re accurate.

There are some important words in there that need emphasis. First, “understood by your teams” isn’t the same as understood by the founder or the C-level. Of course you know what the data means. That doesn’t mean everyone else does. Ask them to explain it to you. You may be quite surprised by the range of responses.

If your teams can’t articulate what their KPIs mean and how they track back to company success, teach them.

The other important word is “perceived”. It’s important because even if your data is solid, if it’s perceived as shaky or inaccurate, the entire data-driven management process is undermined. Trust is critical to belief. Belief is critical to passion. And passion means the difference between striving to think big and settling for incremental gains.

If there’s an undercurrent implicating your data as anything less than rock solid, you need to confront that and fix it. It’s hard to nurture passion from people who value achievement if they don’t believe that your data is an accurate reflection of their efforts.

Meaningful and Trustworthy SaaS Data Comes with Maturity and Scale

I’ve written before on SaaS scale versus SaaS maturity and how that relates to scalability. Data-driven SaaS management seems to follow right along with the maturity curve. Early on, many a SaaS may make many a decision without the benefit of data. In some cases that makes sense because of scale. For example, there’s nothing worse than trying to be a data-driven beast but having too-small sample sizes. That leads to one of two very bad outcomes. One, you actually wait for the data to become statistically relevant (way too long in SaaS time). Or two, you pretend you’re data driven by making gut calls on pathetic sample sizes. Either way, you lose.

The moral to the scale dilemma is not to kid yourself or your teams. Let anecdotal decisions be just that.

If you have scale in your data, you can at least have confidence in what you’re seeing. But maturity can be a very different thing, and it’s where the sweet spot is. I’ve seen immature SaaS companies (with enormous scale) make similar data-driven mistakes over and over again. Usually, those mistakes start with quantity of metrics over quality of metrics. High quantity makes it harder to understand the numbers and maintain their integrity. It’s the immature first reaction to “make the company data-driven”.

The data-driven SaaS management sweet spot is where scale and restraint intersect in a mature and powerful set of growth-driving numbers that everyone understands and believes.

I have a simple way of looking at the sub-metrics that live below the big hairy audacious numbers. If the revenue growth goal of the SaaS company is 10% month-over-month, then every sub-metric below that needs to improve by at least that same rate. That’s always been an easy way for me to justify audacious goals down to the lowest level. It’s easy for everyone to understand the logic that the topline follows what happens all the way down to their personal OKRs. It stands to reason that you can’t expect BHA gr...

Let’s get another cliché out of the way. Talk is cheap. Hmm. In SaaS that’s actually not so true. A lot of talk gets funded. And a lot of decisions get made based on plans (nice, formalized, talk). From there, a lot of evaluation is done based on reporting data (another form of talk). I sit on boards of companies, and even that level of talk is separated from what’s really happening in execution. No, numbers don’t lie. But they often unintentionally or intentionally obfuscate reality. It can be hard to accurately create a SaaS diagnosis of what’s really causing good, bad, or indifferent performance.

Who cares what’s really causing performance?

That’s actually a good question. Who actually cares? Does it even matter? Or is all that matters what’s hitting financial statements? Even if that’s all that matters to the VC, management should actually care about causation. Because blaming the wrong things turns into changing the wrong things and messing up some of the right things. It can be even worse than that — you can indict a model because of execution, or blame execution when it’s really your model. Yeah, that’s heavy. And I’ve seen it play out.

Too few weedeaters.

The trouble I’ve seen only gets identified when you go deep. And most “SaaS leaders” work under the assumption that staying out of the weeds is the path to success — working on, much more than in the business. But here’s the rub. You will find very few SaaS leaders who know (or admit) that they’re actively doing the wrong thing. They will tell you (talk, talk, talk) that they read the right stuff, follow all the best practices, and execute relentlessly. But the only way to know that they are or are not doing those things well, is to validate. And validation happens in the weeds.

When should trust give way to verify?

We should not micromanage and go deep in the weeds to verify everything. In fact, it’s unsustainable and counterproductive to do it any more than we absolutely have to. But when it’s warranted is a tricky judgement call. I use a highly unscientific gut check to feel when things don’t quite add up or align with my SaaS worldview. Obviously, that’s not a scalable nor objective answer. But, it’s kind of true.

Let’s get back to indicting the model versus indicting the execution. This is a good gut check moment. When the space, TAM, and fit appear objectively good, but traction is harder than it should be, look to execution. That means, go as far into the business, as deep in the weeds as needed, to go to verify that it’s not an execution problem. If you dig down there and it’s not, then it may be time to indict the business. But you can’t pull that trigger until you’re sure (via weeds, not reports).

If you do verify that the walking looks more like crawling, then the question is why? Is it people? Process? Management? A lack of one or more of those things? Is the strategy not executable for some fundamental reason? Diagnosing the why behind executional failure is surely a whole other article (or perhaps that’s what SaaSX is?).

We see a lot of executional failure, all the way down to the script level in Sales, the copy level in Marketing, and the playbook level in Support and Customer Success. Some of those gaffes are obvious. Others get obfuscated by smooth talk. Executional problems are all fine, and oh so normal, as long as they’re correctly diagnosed. That stuff’s easy to fix and far less costly than funding a bad model or indicting a good one.

A new sales leader reached out this week to ask when she should hire her first sales development representative (SDR). What a great question, and luckily, it’s a pretty black and white answer.

Let’s start with when it’s not time to hire your first SDR.

It’s too soon to hire your first SDR when:

* You haven’t landed any actual, paying customers yet.* You aren’t certain of your ideal customer profile (ICP).* You haven’t nailed down your differentiation or unique selling proposition.* You don’t know the customer pains you solve, or the needs you fill.* You don’t have a value proposition that resonates with your ICP.* You don’t have a plan for feeding the SDR good leads or providing them a viable mechanism to source good leads.* Product-market fit is still a long way away.

In short, don’t hire SDRs before you figure out the basics. Sales development reps are something you add to a process that is already getting off the ground, not something you do before you are actively selling.

I am not saying everything has to be perfect and written in stone. Because of course in a startup, things shift daily. Ideal customer profile, value proposition, differentiation—these are things that evolve as you learn more about your market and grow.

But, you need product-market fit before you hire your first SDR. Or at least, you need to see that product-market fit is near on the horizon and you are getting very close.

So, when is it time to hire your first SDR?

First, let’s not hire one. Let’s hire two. When you hire one, whether they knock it out of the park or totally fail, you don’t know why. You don’t have anything to compare to. So, it’s always good to hire salespeople in cohorts of at least two in the beginning before you have predictable benchmarks established.

That said, here’s when it’s time to hire your first two SDRs:

* You have an ideal customer profile.* You have a value proposition that is compelling for your ideal customers.* You have some paying customers and you know why they bought, and what problems you solve for them (or what goals you help them achieve).* You have some messaging to help guide the SDR conversations.* You have a fairly firm idea of what makes for a qualified prospect.* You know where your SDRs can get quality leads.

If you hire your first SDRs before you check the above boxes, you will waste money and they will waste time. Even the most experienced & skilled SDRs need a guidepost. They need to know where to find good leads,

SaaS products rapidly evolve with release cycles that feel almost continuous. In fact, some are actually continuous. Regardless of your release cycle, communication is critical to success. And that communication involves the majority of the organization — engineering, product, support, customer success, marketing, and sales. Each team needs clear responsibilities tied to key results in a defined and accountable process. Let’s look at SaaS product feature release go-to-market implications.

Churn and Feature Release GTM Failures

Customers stop paying because of two big reasons: They aren’t seeing value or the product just doesn’t work. Feature release communication can negatively or positively impact both of these churn reasons.

Let’s start with the product just doesn’t work. If it’s broken, and you fix it, but no one knows you fixed it, you might as well have left it broken. This happens a lot. And SaaS companies love to think that sending one email message or in-product announcement means that customers know something has changed. Wrong.

By the same token, if you have high-value features and capabilities that get released, and nobody knows they exist and why they’re valuable, you just wasted all that effort. We’ll take the position that your product roadmap is fed by rapid feedback loops that keep engineering focused on the right things. Problem is, even if all that is true, when the feature release GTM fails, all that effort is fruitless.

Feature Release GTM Common Sense

All too often there’s more effort in feature development than feature communication. And this often starts with failures of translation. No single team within a growing tech company can translate product enhancements into messaging. That’s because the translations are different by team and by audience. What customers need and want to understand is different than what prospects need and want to understand. And sub-audiences also have different agendas. What technical users need may be very different than what business users need. It all comes down to translation of feature dev into the language of the audiences. And there are a lot of them.

But teams can’t translate what they don’t know. So before all this distillation can take place, the fundamentals must be strong. Product must have clear stories and scopes. And engineering must have documented specs and impacts. From those fundamentals, the other release teams can translate into the needs and languages of their audiences and contexts.

SaaS Feature Release Go-to-Market Template

I’ve found a lot of failures in SaaS companies start with missing documentation. That’s not because over-processing is a good thing — it’s not. It’s because the act of writing and having a GTM doc helps you think through touchpoints, impacts, relationships, dependencies, and opportunities.

Get the SaaSX Beacon9 SaaS Feature Release Go-to-Market Template...

Last week I kicked off our SaaS marketing tactics series with attribution planning. Since most SaaS marketing is content marketing, assets are the foundation of success. Managing those assets at scale is incredibly challenging. For those reasons, my tactic du jour is asset tracking. So let’s get to it.

Content Marketing Assets are the Foundation of Your Marketing Value Proposition

In content marketing, assets are the things of value that you have to exchange with prospects over the course of their journey. Some of those assets have higher value than others. Many are timely, others are timeless. Some must evolve over time, while others are evergreen and shelf stable. One thing is for sure, even a nascent startup SaaS will create hundreds of assets per year. And, planning, tracking, and managing those assets is a bear. Do it well and your content marketing thrives. Do it poorly and you’ll lose control in a heartbeat.

Types of Content Marketing Assets

This is by no means an exhaustive list of the types of assets in a content marketing arsenal, but it’s a start:

* Blog Posts (owned, earned)* eBooks* White Papers* Research Reports* Infographics* Interactive Tools (calculators, assessments, report cards, quizzes, configurators)* Webinars* Presentation Decks* Videos (demo, testimonial/endorsement, promo, educational)* Case Studies* Collateral (company, product, solution)

There are a lot of different types of content to track. But what do we need to track?

Asset Tracking Axes

Distribution

Why do you care about tracking all these assets? Because fully leveraging them means they get pumped through your owned media channels, extended through earned media, and amplified through paid media. Translation — they get used everywhere. Asset distribution gets tracked as part of attribution so we don’t need to duplicate that effort.

Maintenance & Performance

And, most assets need to be maintained, which is super painful if you don’t know where they are and how they’ve been used. On top of that, measurement is critical to evaluate their relative performance. Again, where and how they’ve been used is tracked as part of attribution, so we don’t need to rehash that.

Lifecycle

Every asset has a birthday and an owner. Some assets have a sundown or expiration date. Others need regular reviews and updates on a more or less frequent cadence. Some have customer or partner implications. Many have pricing, packaging, or promotional significance.

The content-specific threads that impact an asset’s lifecycle management are legion. This is the missing piece of the puzzle that’s not part of attribution tracking and consequently, routinely neglected.

SaaS Content Marketing Asset Tracker

So we’ve established that asset tracking should happen. And that there are a lot of things to track. But it’s not rocket science. It’s really just an organized, living list of assets. Yet most organizations I see don’t seem to have a handle on what they’ve created ...

I’m working with several companies on the advisory side that have similar marketing challenges around tactics and execution. So, beginning today with SaaS marketing attribution, I’m going to address some of the most common and basic executional failures. The fact is, from CMOs, down to VPs, senior directors, and directors, marketers often have far better intentions than execution. All the data-driven prowess in the world is useless if the data stinks. The oldest adage in the books of garbage-in, garbage-out rears its ugly head in modern marketing every day. So, let’s address the garbage-in side of that equation.

Marketing Data Pipes and the Stuff that Flows Through Them

Getting SaaS marketing data pipes right is hard. You plan your flow; define your fields; set your values; choose your tools, and then implement all of that plumbing. Once you’re done, you’ve got the pipes. But they’re useless until you pump the right stuff through them. Unfortunately, the flow is easier to screw up than the pipes. Why? Because the plumbing is supervised by a small number of higher-level marketing folks, but what gets pumped through the pipes is executed by a larger number of less experienced people. And the oversight on the plumbing is intense, while the flow tends to be neglected in haste when the workload gets dicey (which is pretty much always the case).

That larger group of less experienced people needs tools to help them pump high fidelity data through that shiny data-driven marketing machine. Left to their own devices, most will unwittingly degrade the machine little by little — slowly chipping away at the integrity of what gets sent into the machine. Before you know it, your data-driven machine is a mess, and the reasons it got built get buried in a sea of mediocre, inconsistent data.

SaaS Marketing Attribution Fidelity

Attribution simply means knowing where people and actions come from. The trick to maintaining fidelity is first and foremost having 100% of people fully attributed. First-touch refers to where the came from when they were created. And last-touch means what they did most recently or just prior to a key action being taken. First-touch is critical to understanding where people come from and last-touch is important to understanding what makes them act. You memorialize first-touch forever (as original lead source) and append a running history of last touches.

In order to have valuable, historical attribution analysis and reporting, you need consistent, high-fidelity data. What does that mean? It means you can’t have attribution values change names or structures over time. The path to ensuring that fidelity despite changes in personnel, and variability in tools and versions, is process. How attribution values get set should be as methodically planned as the plumbing itself. And managers with authority need to be able to maintain quality assurance, which means having set rules around the process and a way to verify that those rules are being followed.

This is about super tactical, in-the-weeds stuff like campaign naming structures and UTM values. When it’s planned and tracked, fidelity is high. When it’s left to ad-hoc interpretation, fidelity is low. Low fidelity inputs lead to low fidelity reporting and analysis, which degrade marketing efficacy.

You will spend more to acquire a customer when your attribution fidelity is low.

SaaS Marketing Attribution Planner

All the blog posts (like this one) in the world don’t really help with ...