The UI tax: why software should work where you do

Why software should work where you do

I think we're reaching a point where customers will stop accepting that using a piece of software means working inside it.

If you want to understand how your affiliate programme is performing, you should be able to ask that question in the tools you already use. Having access to the answer shouldn't depend on knowing your way around another dashboard.

That might sound like an odd position for someone who runs a software platform. We've spent years building an interface to help people manage their partnerships and understand their performance. There's real value in that work. But we also need to recognise when the way we've organised our software becomes extra work for the people using it.

What is the UI tax?

Our marketing stacks have become enormous. Each product has its own navigation, reporting conventions and version of what your working day should look like. Individually, those products can be useful. Together, they leave you doing a surprising amount of work just moving information around.

That's how I think about the “UI tax”. You pay it in time and attention whenever you have to navigate a system, rebuild a report or export a file before you can get on with the work you actually intended to do.

We've become so accustomed to that process that it can feel like an unavoidable part of the job. I don't think it will stay that way.

How AI is changing what you expect from software

AI is changing what people expect from software. When you can ask a follow-up question, change the comparison or reshape an analysis in a conversation, going back to a fixed set of menus starts to feel restrictive. The question becomes why you have to adapt your thinking to the software, when the software could do more to adapt to you.

CRM systems make this particularly clear. Your team enters the customer information, records the conversations and keeps the records current. You then pay for a system that helps you manage and use it. That's a reasonable exchange, provided the system makes that information more useful. It becomes harder to justify when getting it back out, or using it somewhere else, creates another project.

A CRM does much more than store records, just as an affiliate platform does much more than display transactions. Permissions, workflows, reliable tracking and consistent definitions all matter. Making data easier to access raises the importance of those foundations, because you need to trust the information wherever you use it.

What I question is the assumption that the company's own interface should remain the main way you get value from them.

Why this matters for affiliate marketing

That question matters for affiliate marketing because so much of our work sits between data and relationships. You look at performance to decide which partner to call, where to invest or what needs attention. The report is useful because it helps you make that decision.

Imagine preparing for a conversation with an affiliate whose sales have fallen. You might want to compare recent performance with the previous period, look at the offers that were running and consider your own campaign notes. Those pieces of information may sit in different places. Bringing them together can take longer than deciding what you want to discuss.

With the right connections, you could explore that information in the AI workspace you already use, ask a follow-up question and prepare your conversation there. You would still need to speak to the partner to understand what happened. A model's explanation of a sales decline is a hypothesis to investigate, and the relationship gives you context the report can't.

For me, that's a useful role for AI in our industry. It can reduce the preparation that sits around relationship work and help you arrive better informed.

Giving you more freedom over your analysis

It also gives customers more freedom to decide what useful analysis looks like. We can build reports around the questions we expect you to ask, but we won't anticipate every combination of priorities, budgets and business context. An agency, an advertiser and an affiliate can look at similar data and need very different things from it.

You should be able to choose the comparison, shape the output and bring your account data alongside other information you're authorised to use. That makes access valuable to people who know the right question to ask but don't have the technical skills to build an integration or prepare a complex spreadsheet.

What is Model Context Protocol (MCP)?

This is where Model Context Protocol, or MCP, becomes relevant. It's an open standard for connecting AI applications with external data and tools. It gives software companies a way to make their capabilities available through compatible AI assistants.

Our upcoming MCP release reflects that direction, as do our Slack and Microsoft Teams integrations. They come from the same belief: partner marketing should fit into the way you work.

I don't think every customer will want to run their programme through an AI assistant. There are plenty of tasks where a dedicated interface makes sense. The important change is that you have a choice, and we take responsibility for making that choice useful.

Rethinking how software companies measure success

For software companies, that means being willing to question some familiar measures of success. Time spent in a platform can mean someone is engaged. It can also mean they're struggling to find an answer. More visits and more clicks tell us very little without understanding what the customer accomplished.

I'd rather someone get the information they need quickly, use it confidently and make a better decision than spend an afternoon navigating our reports.

There's a commercial question here too. If we make data easier to access and then surround that access with unnecessary restrictions or pricing that discourages use, we haven't done much to improve the experience. Platforms still need sustainable businesses. The value we charge for should be clear in what we help customers achieve.

What this means for Commission Factory

For Commission Factory, the challenge is to make our data, tracking and partnership infrastructure useful wherever you choose to work, while preserving the accuracy and context that make it worth using.

We'll need to earn our place through the quality of that contribution. Customers will judge us by whether we help them build stronger partnerships and get better results, and we should make that as straightforward as we can.

The future of our platform should give you more freedom over how you work. It shouldn't require more of your day.