5 Data Trends for 2024, and one key theme
Data teams do best when they enable GTM teams to shine. Read: "Everything Starts Out Looking Like a Toy" #182
Hi, I’m Greg 👋! I write weekly product essays, including system “handshakes”, the expectations for workflow, and the jobs to be done for data. What is Data Operations? was the first post in the series.
This week’s toy: solid-state batteries are coming, and when they do, they will allow us to charge tech a lot faster. No one thinks they will replace other kinds of batteries … yet. But when they do, it will change the game.
Edition 182 of this newsletter is here - it’s January 22, 2024.
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The Big Idea
A short long-form essay about data things
⚙️ 5 Data Trends for 2024, and one key theme
I’ve been looking back at the essays I wrote in 2023, and thinking about how they will inform my thinking for this year.
One key theme stands out: how do you do more with less?
That doesn’t necessarily mean 2024 will be a year where you do less. It means that as a data operations or revenue operations team, you need to align your work with the key challenges of the business so that you can advocate, present, and be proud of the work you and others are doing to enable your team.
Perhaps you’ve aligned yourself to this reality already.
Here are a few ways data teams can support, enable, and turbocharge GTM teams in 2024.
Answer business questions. This one might sound obvious, and it’s key to ground your analysis in the question: what business problem are we trying to solve, and why? If you can’t identify a relevant business question, this might not be a high-value problem to solve.
Creating new automation or improving existing automation to improve process. If you have Service Level Agreements for tasks that need to get completed in your org, you need some level of automation to help you know how you’re doing,
Using the same metrics as the rest of the business. A data team is effective if the team believes that the data is accurate, timely, consistent, and has high quality. The best way to do that is to use the same metrics as the rest of the business instead of fragmenting analysis into new definitions.
Theory => Practice
What are the tactics that will help you to achieve these goals? They look pretty mundane, but add up over time to produce results.
A regular cadence of information is important for predictable analysis. This could look like daily or weekly reporting fed by an automated process. Whether you are measuring a cohort-based approach for sales or a time-based approach, make it easy for stakeholders to find this month’s or this week’s information in a minimum number of reports.
Interrupt-driven alerts help you understand when to take action. When you get a message in Slack with an at-mention, you should know where to go, what to do, and how to respond. When a known problem happens, use the known solution, or document a new one when you find one. (These can be positive too! Don’t forget your #wins).
You might need detailed reports for deeper analysis. A pacing report, a detailed list of account MRR movements, or a source-based analysis can give you a sense of what’s going on over a longer time series or a different slice of data. This is important when your business is seasonal or when the leads behave differently contingent on their source.
5 Data Trends for 2024
With these tactics in mind, what are some data trends you should be watching in 2024?
Enabling each rep to do more with the resources they have
Data teams provide the details that reps need to manage their pipeline, particularly when it comes to summarizing information and helping them to build lists and compare performance over different time periods.
In this context, “scale” means defining a consistent process that will help any rep to get better, not just your best performing ones.
Some tools that can help here:
Pacing graphs to show the performance of this month or this quarter against your own performance from previous periods
Pipeline analysis to know which reps need support and when in the sales cycle they should be accelerating or giving up on a deal
Automatic reminders to do the things you should be doing
We all know we need to eat our vegetables (or whatever other metaphor you want to use). It helps when it’s the computer or an automated process telling you the best next action instead of a daily task you have to do.
By shortening gaps between required activities, velocity improves for the whole pipeline.
Here are a few ideas for automation:
Scheduled queries to push reminders to close tasks
Round-robin assignment of accounts to distribute the load
“The Little Things”
Tactical steps that don’t scale to get to scale
Your best reps manage to do things a little differently. By tapping some of their smarts and building tools to provide scaffolding, you can help the entire GTM team gain the benefits from these behaviors.
Data teams can help here by:
providing “canned links” to automated account research
use a “Clean Your Room” dashboard to show where the everyday work needs to get done
Data Structure to Assist GTM
Building the models that make tactics possible
How do you build a structure that helps your team as the product changes? One way is to extend the tools you have already to support the usage of new features using the same format.
Data teams enable GTM with these actions:
when new product features are added, build new models to assess usage
demonstrating how feature adoption varies with different pricing models
AI for GTM that makes sense
Where can you leverage AI and not depend on it being perfect
In 2024, everyone is curious about the right way to use AI. In GTM, you want to use AI for areas where it’s not prone to hallucinate, and also where it doesn’t need to produce the same result every time you ask it a question.
These actions look like the kind of tasks you would assign to a person who is always available and does a “good enough” job. The results will not wow you using AI but they remove a lot of risk to using AI.
Low-risk, high-reward uses of AI look like:
summarization of meetings
adding context based on keywords prospects say
summarize product feedback into clusters of requests
I’m looking forward to revisiting these themes this year!
What’s the takeaway? The key theme for data teams in 2024 looks very similar to the one that made data teams successful in 2023: focusing on the activities and reports that matter. By focusing on the same metrics as the GTM teams and making incremental improvements, data teams can help improve and speed up the scaling motion.
Links for Reading and Sharing
These are links that caught my 👀
1/ The hot hand 🔥 - is a streak counter motivating or de-motivating? Either way, it’s an effective way to get your attention. Using a counter raises the stakes by promoting loss aversion. If you lose this streak, will you get it back?
2/ Building a kit template - If you’re building a tool, you might need a template. Venkatesh Rao suggests the blueprint you need to build for any tool. What I like about this kit? It’s meta → and suggests a kit for building kits.
3/ Making venn diagrams with text - I love the idea of building diagrams with text. It makes the diagrams easier to read, opens up the possibility of using LLMs to summarize and create them, and allows you to store them in source control. Penrose is a new example of this genre.
What to do next
Hit reply if you’ve got links to share, data stories, or want to say hello.
The next big thing always starts out being dismissed as a “toy.” - Chris Dixon