INBOX INSIGHTS, November 13, 2024: Validating Ideas With User Stories, Everything Can Be Measured - Trust Insights Marketing Analytics Consulting

INBOX INSIGHTS: Validating Ideas With User Stories, Everything Can Be Measured (11/13) :: View in browser

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Validate Marketing Ideas With User Stories

Disclosure: Katie is traveling for MarketingProfs B2B Forum this week, and so we took the transcript from our workshop, extracted a relevant portion, and with Anthropic Claude Sonnet 3.5, had it generate this week’s newsletter from Katie’s actual words at the workshop.

You know that feeling when you wake up with what feels like the MOST AMAZING marketing idea ever? The one that has you reaching for your phone at 3 AM to send a Slack message to your team because you just can’t wait to share it?

Yep, I’ve been there too. More times than I care to admit.

But here’s the thing – as a recovering project manager who has managed agile development teams for years, I’ve learned that enthusiasm doesn’t always equal effectiveness.

Let me share a little behind-the-scenes story about how Chris and I handle these “brilliant” ideas at Trust Insights. It’s actually kind of embarrassing how often this plays out:

Me: “Hey Chris, I have this amazing idea we should totally do!” Chris: “Okay, put it into a user story.” Me: Pause “…Never mind, it was a terrible idea.”

Sound familiar?

The thing is, I’m not actually giving up on ideas – I’m saving us time, resources, and potential frustration by using a simple framework borrowed from software development: the user story.

What’s a User Story Anyway?

A user story is a three-part sentence that forces you to think through: 1. Who needs this thing (the role) 2. What they need to do (the task) 3. Why they need it (the outcome)

The format is simple:

“As a [role], I need to [task] so that [outcome]”

Why It Works for Marketing

Here’s what makes user stories so powerful for validating marketing ideas:

They force you to identify your actual audience (not just “everyone”)
They make you articulate what you’re really trying to achieve
Most importantly – they require you to specify the concrete outcome

That last part – the “so that” – is where most marketing ideas fall apart. And that’s a good thing! Better to realize it now than after you’ve invested time and resources.

It Works For Everything

The beauty of this approach is that it works for any idea. Sometimes Chris will come to me excited about a new technical innovation he’s created (like an automated playlist curator). So I’ll ask him to put it into a user story format:

“As a [target audience], I need an automated music curator so that…”

And that’s where we get stuck. Because while the technology might be cool, if we can’t articulate why our audience needs it or what problem it solves, it’s probably not worth pursuing right now.

How to Use This Today

Take your current marketing idea or campaign
Try to write it as a user story
If you can’t complete all three parts clearly, that’s a red flag
If you can complete it, use the outcome to define your success metrics

The next time you have what feels like a brilliant marketing idea, try this approach. You might find that some ideas don’t make it past the user story stage – and that’s okay! It’s much better to figure that out before you’ve invested resources.

And if you’re like me, you might find yourself having this conversation in your own head before you even bring ideas to your team. (Which, honestly, has probably saved my team from having to sit through some pretty questionable brainstorming sessions.)

Remember: No matter how exciting an idea seems at first, if you can’t articulate who needs it and why, it might be time to go back to the drawing board. Or in my case, back to sleep at 3 AM instead of sending that Slack message.

What marketing ideas have you gotten excited about that didn’t quite hold up under closer examination? Reach out and tell me, or come join the conversation in our free Slack Group, Analytics for Marketers.

– Katie Robbert, CEO

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In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss the crucial topic of AI readiness for businesses. Discover the essential steps to determine if your organization is truly prepared to leverage AI effectively. Learn how to avoid common pitfalls and misconceptions surrounding AI implementation. Gain valuable insights into maximizing your AI investment and driving tangible results, rather than just chasing innovation awards. Prepare to rethink your approach to AI and unlock its true potential for your business.

Watch/listen to this episode of In-Ear Insights here »

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In this week’s Data Diaries, let’s recap a brief reminder that arose during our MarketingProfs B2B Forum workshop this year.

When we talk about using data to make decisions, to be data-driven, we’re not just talking about spreadsheets.

Let’s say you want to understand your competitors better, do some competitive analysis. What data would you use?

Certainly, you could use quantitative data like traffic analytics from a tool like Semrush or AHREFS, or use social media data gathered from a tool like Brand24 or Talkwalker. Those would be valid sources to understand a competitor’s marketing.

But one of the most valuable data sources you have is probably going untapped:

Your sales calls.

For organizations that have salespeople who call prospective customers and speak with them, email them, chat with them, etc., you have a massive treasure trove of competitive data. Think about it – you have calls where someone – let’s call her Alice – is talking to a prospect and things just don’t work out.

Alice: So Devin, did you get a chance to review the proposal I sent over last week? What did you think?

Devin: Yeah, uh, I just don’t know. I mean, it seems like Acme is a good fit, but Beta just has more features.

Alice: Which features, specifically?

Devin: Well, they do buy me dinner a lot.

Using a generative AI tool like Claude, ChatGPT, or Google Gemini, you could extract enormous quantities of useful data about competitors that can guide your overall strategy. In the silly example above, a data analyst using generative AI would identify that Beta Corporation’s sales tactics are creating pressure on Acme, and Acme might need to pivot how they do sales, if this theme is recurring in their call logs.

The key question is: do you have the data? And if so, is it accessible to you so that you can use it with the AI tools you have access to and garner insights from them?

Data is more than just spreadsheets and numbers. It’s any useful information, anywhere inside or outside your company. The more valid, relevant data you have, the more powerful your analysis can be – but you first have to recognize just how much data you have that you could be using.

Here’s a roundup of who’s hiring, based on positions shared in the Analytics for Marketers Slack group and other communities.

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