Welcome back to Forests Over Trees, your weekly tech strategy newsletter. It’s time to zoom-out, connect dots, and (try to) predict the future.

This post is a special edition deep dive, brought to you in partnership with Ahrefs.

A Rabbit Hole of Tech Wisdom

An Ahrefs feature deep-dive

A few days ago, I went down an internet rabbit hole.

And it wasn’t a situation where I regretted it and wished for my time back.

No, this was the kind of rabbit hole where I wish I had someone there with me, to be inspired and to debrief on all the lessons learned.

Luckily, I have you!

How it Started

It all started when I was researching Ahrefs’ Content Changes feature.

If you’re not super familiar with what Ahrefs does, here’s a quick blurb from a prior post:

…and their Content Changes feature is like a cherry on top. It’s basically an analytical time machine.

The Feature

If you make changes to your own page, you can track those versions and how they impact traffic to your site or to specific pages. But you can also do that for competitors’ pages, so you see if a major upgrade to a page (or a new blog post on their site) is creating a boost to their traffic.

Here’s an example, using one of Ahrefs’ blog pages. In this view, the tool highlights changes between snapshots that were taken on particular dates (and color-codes the date graph based on how drastic the changes were!).

But you can also start by looking at traffic changes, then dive into any content changes that happened around the same time. In this second view, those green dots represent content changes.

So we can see that those changes from mid-2023 had a hugely positive traffic impact!

Pretty helpful, right?

But that’s just the tip of the iceberg.

The further I went down the rabbit hole, researching the feature, the more I became convinced that this is really smart for Ahrefs and their users…  

…and I started to see lessons for other founders and builders here.

Lesson #1 – Experiments make dollars and sense

According to a Harvard Business Review research paper, experimentation is critical to improved decision-making and higher revenue. As one example, Microsoft’s Bing used experimentation to identify and test hundreds of improvements, which ended up boosting revenue per search by 10%+. As another example, Amazon ran tests to identify the relationship between the difficulty of a game (Air Patriots) and its popularity, and ended up shipping a slightly easier version that increased play-time and revenue by 20% each!

Ahrefs is smart to build Content Changes and give their users similar performance-boosting power.

In the short term, users can analyze the relationship between page changes and traffic, rolling back changes that cause negative impact or doubling down on the ones that are positive.

So it takes out guesswork and helps those users decide – and move – faster.

But it also has long-term benefits. Over time, the data-driven mindset of that one user becomes infectious (in a good way). By demonstrating the positive ROI of running experiments and tracking the data, they subconsciously give their teammates permission to do the same. This can create compounding benefits for the team.

Lesson #2 – Competitive (but not obsessive) intelligence

Tech is notoriously competitive…

Databricks paid for billboards that called Snowflake slow and expensive. Apple’s Mac vs. PC ads tried to make it uncool to be a PC-lover. And Elon and Zuckerberg almost had a literal cage match a few years ago…

Given those competitive dynamics, you need to stay informed about what competitors are doing, but you want to avoid letting it become an obsession.

So instead of obsessing over competitors’ every move, and second-guessing your own strategy, Ahrefs’ content changes feature lets users put that competitor monitoring on auto-pilot.

Then, when there’s a large shift in traffic to specific competitor pages, users can immediately pinpoint what drove the change in traffic, and decide whether or not to react.

Not every competitor action needs a response! Ahrefs helps users balance competitive intelligence with the ability to stay focused on their own content and messaging.

Lesson #3 – Centralizing tools for users

When tech product teams are considering what to build for customers, it’s smart to analyze a customer’s journey – the steps they take before, during, and after using a product.

Customer journey mapping often exposes ideas for how to remove or simplify steps for users.

One super common example of that is called platform envelopment. You take a step previously performed outside your product and add it as a feature.

Here’s a visual:

For Ahrefs, they must have noticed how many of their users relied on the Wayback Machine to retrace (internet) history. Users would have used Ahrefs for traffic monitoring and analysis, but then had to go to the internet archives, confirm the dates of each major content change, reconcile those dates against the traffic patterns from Ahrefs… and repeat that process for multiple pages on their site…

Even just typing the steps, that sounds like a lot of work. By embedding a version of the internet archive directly into Ahrefs – and auto-magically overlaying traffic analysis on top of content change dates – they’re delivering a ton of value to users.

Wrapping up

We hope you’ve enjoyed this breakdown. There are always lessons to learn about how products got built… lessons that you can borrow or steal for your own work.

If you want to go even deeper on Ahrefs’ content changes feature, this blog from their team is a good starting point. If you find other nuggets of wisdom there, reply to let me know!

In the meantime… go experiment, avoid obsessing over competitors, and map out your customers’ journey.

Good luck, people!

The forest is growing.
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