👋 Hi, I’m James. Thanks for checking out Building Momentum: a newsletter to help startup founders and marketers accelerate SaaS growth through product marketing.
When I talk to startup founders, marketers, and commercial leads, they’re nearly always rushing around trying to do a hundred things at once. Everything is important, everything is a priority, and everything just requires work.
Their biggest challenges often arise from just two main causes:
Lack of customer insight – who are they, why did they buy?
Lack of market insight – what’s the landscape, who are the competitors, why do we lose to them?
To make progress and overcome these issues, the only answer is to spend more effort doing more work. Inescapable work that has no shortcuts. Work that enables more important high-value work, but requires time-consuming labour to carry out.
This work usually manifests in these ways:
Reviewing their customers and prospects to find patterns
Win/loss research to discover why a customer did or didn’t buy
Evaluating competitors and building an over-complicated spreadsheet
In this post:
Three product marketing systems to set up now
As in many other functions, I expect we’ll see the rise of ‘product marketing operations’ – a specific role designed to help PMM teams operate as efficiently as possible. The PMM Ops role will build scalable systems to take data and research, develop summaries, and provide usable outputs to PMMs and other teams with go-to-market, customer, competitor, and sales insights.
And just as product teams move away from project-based research to continual research, product marketing teams must do the same.
Here are three key product marketing operational systems that any startup marketer can set up and start making better decisions with reliable insight.
1. Reliable CRM prospect and customer data
Not enough sales/marketing/success teams work on data sanity in their CRM, missing out on the benefits from clean data. But when implemented and used, it becomes a really strong indicator of patterns and insight for tactical and strategic decisions.
In addition to the standard CRM data (like industry, company size, etc), you’re going to want to capture key fields at different object-levels that help you make better decisions. These will depend on your context, but generally look like this:
Lead stage – capture information on ‘fit’ indicators like tech used or anything else that might indicate they are your ICP
MQL stage – capture info that represents their challenges and motivations
SQL stage – capture fields that tell you more about their buying process, key selection criteria, mindset
Opportunity (early stage) – capture key decision-making criteria, their buying role, what they are trying to achieve, competitors in play
Opportunity (later stage) – capture their reactions, must-haves, information on the project’s priority, product feedback
Opportunity (closed) – capture their expectations of the partnership, as well as your CRM win/loss data
It’s key to make it really simple for sales to record data: there are Slack bots that can do this, or you can set up reminder emails using your CRM to remind reps to add the information required at each stage. You may need to add a data completeness spiff to your sales rep’s comp to ensure they add as much richness as possible.
This data serves as indicators of patterns, it won’t provide all the answers. But make sure you use it. Set up monthly or quarterly reports that go not just to your immediate team but also leadership. Create a Slack channel that posts each field in real-time to provide a pulse check into your deal flow.
2. Automated NoWL interviews
I’ve written before about win/loss processes and how valuable they can be, but most companies don’t know enough about top-of-funnel issues which can have a bigger impact on direction and strategy. It’s really valuable to include prospects who said ‘no’ at some point prior to opportunity in your research process.
I call this process NoWL, standing for No, Won, Lost. Check my previous post on win/loss for suggestions on how to set an automated system up, and how to make the most of the insight.
3. Competitor intelligence (CoIn)
Nearly every company I’ve worked at has tackled competitor intelligence in the same way: given the lowest paid person the job of creating a big spreadsheet that captures all their features, marketing, and pricing information.
This spreadsheet is summarily resigned to live in a Google Drive folder that’s never used.
Competitor intelligence should be usable and help with decision making by product, by sales, or by marketing. It should not be about creating a bible of information – it will never be socialized or used effectively.
Think about how different teams need competitor intelligence, and work backwards from there. For example:
Sales teams need competitor landscape info for initial training, battlecards for regular updates, and real-time insight on how to beat them
Product teams need general landscape knowledge, information on their market, and their unique claims; feature insight can be gleaned later on a project basis
Marketing teams will need general landscape knowledge, how they differentiate, and their awareness in the market; marketing tactics can be evaluated later
This might lead to three pieces of work:
One-page overviews of top competitors, their place in the landscape, who their market is, and how well known they are
Summarised battlecards of key messaging and our defensive/offensive game plan against them
Real-time insight to allow teams to react (or be proactive) to updates
With small teams who have a lot of shared domain experience, it’s often most effective to start in reverse order.
Build the real-time feed using a Slack channel and space for discussion on sales insights, auto-post reviews for them from G2 or Capterra, send Google alerts straight into the channel
Assign someone to spend a day on creating battlecards, and iterate monthly with direct feedback from sales
Assign someone a week to create the first draft of a competitor overview before making it part of someone’s regular responsibilities
Build systems and processes as early as you can
Building a regular system of build, use, learn to iterate quickly is much more effective than revisiting behemoth documents twice a year.
You’ll have less manual work on your to-do list while using current, up-to-date insight to drive better decisions and react quickly to market changes.
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