Better demos create a win for prospects and your sales team
"Everything Starts Out Looking Like a Toy" #76
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Hi, I’m Greg 👋! I publish this newsletter on finding data products and interesting data observations with the goal of finding patterns and future product insights. (Also, it’s fun.) If you need a background on how we got here, check out What is Data Operations?
This week’s toy: Wordle - a simple word game that’s not that simple. What’s fun about it? Play is very limited (only 6 chances to guess, can play only once a day), and Wordle has a built-in sharing mechanic. So far, I’ve got a three day streak going. Edition #76 of this newsletter is here - it’s January 10th, 2022.
The Big Idea
A short long-form essay about data things
⚙️ Building a data-driven demo
One of the hallmarks of Product Led Growth (or “self-guided trial” if you’re old-school like me) is the ability for trialers to get their hands on the product and try it out themselves. Trying a product with no guardrails, however, produces a lousy experience if you don’t have a use case in mind. You might end up spending lots of wasted time configuring a feature or an area that you don’t need.
Here’s the challenge: you want the trial prospect to get their hands on the product. You want them to be able to complete an example use case within a reasonable amount of time, but probably don’t want them to be able to do everything the software can do without talking to someone (read: sales) about how to maximize their experience.
At the same time, you don’t really know much about your trialer and want them to have a good experience in a controlled amount of time.
Creating guardrails for the user
The first thing you want to do in your demonstration environment is to create some boundaries for your prospect. If the capabilities to limit the user don’t exist in your product, create some artificial boundaries by telling the customer what you want them to do.
This means thinking about the ideal demo scenario to show:
A small number of steps to complete a realistic scenario
The exact steps in the product to get that done
What it should look like when the action is completed
If you are able to diagram or list these steps, you’ve got a good candidate to automate the demo scenario for the customer. But what if (like many products these days) you need to confirm that data is in place within the test instance for the user to have a good experience? You need to think about what data set you need to load, how to load it to get started, what it should look like after the steps are completed, and how to “reset the environment” in case the prospect wants to try again.
Building a dataset that works
Start with a simple task. In an automation software example, you might want to match sales leads with accounts you already know about. Lead-to-account matching - at its core - is the process of mapping information about the lead to an account or company that you already have in your system.
The steps to this involve looking at the email address or company name of a lead list, looking up an account website or an account name from your account list, and aligning the lead with the appropriate account.
To handle this, you need to have:
A list of leads (perhaps a limited set of fields, like first name, last name, email, company, and title)
A list of accounts (with name, website, industry)
The sample data for each that will allow the customer to follow the instructions and reach the desired result
This data needs to be in place for the prospect to achieve the desired result. This means that building the demo path has to include some notion of loading the data. (SPOILER: it’s easier if you load the data for them and tell them where to find it.)
Designing the “happy path”
What does it mean to create a great demo experience for a prospect?
They should be able to follow a set of steps, execute those steps, and see the result of their actions within a short period of time. Doing these steps should provide an example of the type of thing they need to do (or would pay to do) in the app should they decide to buy.
Simply put, a great demo forces the prospect to make a decision about whether to buy that product. If you see the value, experience the value, and understand the value in a set period of time, that’s a Product Qualified Lead that either needs to end in a sale or a good conversation with sales.
And why do you need to be able to reverse it and load fresh data in a brand new instance? That’s the essence of a demo that your sales team can use over and over again. The act of designing the “happy path” also highlights the experience your sales team needs to have. Who benefits? The prospect.
What’s the takeaway? Building a demo for prospects to use unattended overlaps with the same effort to enable your sales team in a product-led motion. Add the ability to load and reset the data and you have a powerful tool for a data-driven team.
A Thread from This Week
A Twitter thread to dive into a topic
Kyle McDonald shares some eye-grabbing images that show what AI can do with a prompt. Things have gotten … a lot better and fast. (Raises the question of how to prove authenticity or “this was made by a person”)
Links for Reading and Sharing
These are links that caught my 👀
1/ nbd - Just the guts of a spreadsheet in code. David Singleton decides to build a program that does most of what a spreadsheet does in a weekend. The point of this is not to point out how easy or hard this should be to create a fully realized product, but rather what happens with a very focused specification against a well-known problem. Building features is the start: solving specific use cases is even better.
2/ You wouldn’t believe what happens next… - Everyone wants to make content that drives views. Rand Fishkin has a theory on how to make that easier, providing the Hook, Line, and Sinker approach. The story of how he got to this theory is interesting too; Rand is excellent at telling a yarn. You need to read this because we’re all writers now, and need to pay close attention to the key elements of attention grabbing.
3/ Swimming to infinity - Scientists have created “robots” that work continuously in liquid. The possibilities of improving drug delivery or changing the way that chemicals are filtered from industrial accidents are super interesting. Using the basic principle of powering buoyancy through chemistry sounds simple, but is obviously amazing when triggered remotely. Cool!
On the Reading/Watching List
Some things to watch or read, in no particular order
Watching: Here’s a quick video on building confidence.
Reading: We all need a little encouragement at the beginning of the year (or at any time in the year, really.)
Beth Pickens writes about getting through, no matter what else is going on in your life. Making art is one way to do something every day and make a difference.
What to do next
Hit reply if you’ve got links to share, data stories, or want to say hello.
I’m grateful you read this far. Thank you. If you found this useful, consider sharing with a friend.
Want more essays? Read on Data Operations or other writings at gregmeyer.com.
The next big thing always starts out being dismissed as a “toy.” - Chris Dixon