“I have the data. I just don't know what it's telling me or what I should do next.”
Running a small business means wearing a lot of hats.
But being a full-time Meta Ads analyst probably shouldn't be one of them.
One thing we kept hearing from solopreneurs and small business owners was:
“I have the data. I just don't know what it's telling me or what I should do next.”
And that's exactly what we're trying to solve with Xolora.
Instead of spending 45 minutes jumping between Meta dashboards, tabs and reports, Xolora helps you get to the answers faster.
A few things we've built around that idea:
→ Bring someone else in
Invite your VA, team member or partner to help with campaign analysis.
→ Get there faster
Use Cmd+K / Ctrl+K to jump directly to the metric or action you need.
→ Know what to ask
Type / in the AI chat to get suggested prompts based on your actual ad data.
The goal isn't to give you another analytics dashboard.
It's to make marketing data easier to understand and act on — especially when you're running the business yourself.
One of our beta testers described the experience like this:
“I really like how simple everything is. I didn't need to spend time trying to figure things out. I knew where to click almost immediately, and the whole process felt smooth.”
We're currently running the beta and I'd love to test it with a few more solopreneurs and small business owners.
If you'd like to see, how it helps you, click the link below.
This is the analytics trap in one sentence: more data, same confusion.
A metric is only useful if it changes a decision. If the dashboard can’t tell you what to stop, start, or test next, it’s mostly expensive wallpaper.
Exactly! And yet most dashboards fail at it. Especially my target audience (solopreneurs and small business owners) needs a dashboard that speaks their language. That gives them clear next steps.
The quote you pulled -- "I have the data, I just don't know what it's telling me" -- is one of the most common things I hear from founders and small business owners who are running paid ads for the first time. The problem isn't access to data. It's that Meta surfaces a hundred metrics and none of them say "stop this ad" or "scale this one" in plain language.
The "know what to ask" feature with suggested prompts is the right direction. Most people don't fail at reading analytics because they're not smart -- they fail because they don't know which question to bring to the data. Surfacing the right questions based on actual campaign state is a much better onboarding than a tutorial.
The Cmd+K shortcut is a small thing that will matter a lot for the type of person who sticks with a tool long-term. Power users remember those.
Curious how Xolora handles the moment when data is genuinely ambiguous -- for example when ROAS looks fine but the winning campaign is cannibalizing a higher-margin product line. Does it surface those kinds of cross-metric conflicts, or is it focused on single-metric clarity for now?
The goal of Xolora is to lower the bar and make marketing accesible for solopreneurs and small business owners which are a highler-underserved niche. While building we always had one question in mind: What would make it easier for them? When you build a tool with the user in the center, you'll end up building a successful one.
The daily unit should be a decision card, not another chart: what changed, likely drivers, evidence, confidence, recommended action, and the metric that will confirm or reject it. Meta data is noisy, so the product should also say when there is not enough evidence to act. Preventing a bad budget change can be as valuable as finding a winning ad.
It does say when there is not enough data to act.
That is important. The next test is whether it names the missing evidence and the cheapest next action that would make the decision possible. Not enough data is useful; here is the one measurement or comparison that would change that is where it becomes operational.
This is such a common gap — having the data isn’t the same as having a read on it, and most dashboards don’t tell you which numbers actually matter versus which ones are just noise. What’s the data source you’re staring at — is it more a “too many metrics, no clear signal” problem, or “I have the numbers but don’t trust what they’re implying”?
Last year I surveyed solopreneurs and small business owners and 80% said they didn't know their marketing KPIs and if they did, they wouldn't know what to do witht them. So it is not really a matter of trusting/not trusting the numbers, but really being clueless.
The gap between data and action is exactly where an analytics product earns its value. I like the idea of suggested prompts based on the actual account state because many small teams do not know which question to ask. One thing I would make explicit is the evidence behind each recommendation: metric, time window, confidence, and what would falsify it. We use a similar user-controlled pattern in Speechara.Ai: suggestions are useful only when the person can inspect, edit, and choose whether to use them. How do your beta users react when the data is genuinely ambiguous?
Yes, I was thinking the same. A blank chat can feel intimidating for someone who doesn't know marketing. Suggested prompts lower the bar.
The "know what to ask" part is the piece that stands out to me. Most ad dashboards assume you already know which number matters this week. I am curious how you handle the false positive side of that, where a metric moves but it does not actually mean anything worth acting on. That is usually where solopreneurs either overreact to noise or give up on the tool completely because it cried wolf too many times.
The false positive is based on the industry's average KPIs. So if the user is active in industry X, the data is analyzed against industry benchmarks. And of course, it's AI and no AI (and no human) can be 100% correct on that.
The gap between information and action is exactly where good analytics earns its value.
Indeed. And yet so many tools focus more on information, assuming the user knows how to act. But for a small business owner or a solopreneur that can become a bottleneck. That's why it was important for me to build a tool that gives them actionable recommendations, so they can get confident with their marketing decisions.
The phrase "what should I do next" is the important wedge here. For small-business users, I would make the first win narrower than "understand your ads": pick one recurring decision, like pause, raise budget, rewrite creative, or wait.
If the beta can consistently turn messy campaign data into one confident next action, the dashboard becomes much easier to sell because the promise is no longer more insight. It is less decision fatigue.
Thanks for your recommendation.
The wedge could be prompts based on real ad data. Each recommendation should show the metric behind it, the threshold it crossed, and what result would prove it wrong. That gives a solo owner enough context to act without making them learn Meta Ads. A short decision log would help, too. They could see which recommendations worked instead of starting from scratch every week.
Those are good ideas. Thanks for sharing.
Let's see what our actual testers think. Based on their feedback we'll improve the tool.
The VA or team member invite is the detail worth pushing on. Solopreneurs already know a second person could interpret the dashboard for them, that part is not new. What is new is knowing when that second set of eyes actually catches something you would have missed versus just agreeing with the AI chat. In the beta so far, has the person someone invited ever flagged something the suggested prompts did not surface, or is the feature mostly about splitting the labor right now rather than adding a different kind of judgment?
So far I don't think any tester invited a second person to their organization.
But the feature is more about splitting labor, as solopreneurs are very busy.
I like the framing here: the problem isn't lack of data, it's the gap between having information and knowing what decision to make from it.
I'm curious how you think about the boundary between AI suggesting an action and actually giving enough reasoning for a small business owner to trust that recommendation.
That's why we have a chat so the user can explore the reasoning more deeply. And our chat is highly focused - it only talks about Meta ads.
That makes sense. I actually like the focused scope — it probably makes it much easier to keep the reasoning grounded in the actual data rather than giving generic marketing advice.
The part I’d be interested in is how you handle recommendations when the underlying data is ambiguous. For example, if two different actions could reasonably explain the same signal, does the chat surface the uncertainty and the evidence behind each option?
I think that distinction between “here’s what I recommend” and “here’s what the data supports, and here’s where I’m still uncertain” becomes really important when AI is helping with decisions.
That's why we plan to connect GA4 after beta. So ambiguitiy gets dissolved.
The interesting part seems to be the gap between making data easier to understand and actually knowing which action the data justifies.
How are you thinking about keeping Xolora from becoming another dashboard that simply explains the numbers?
First of all, I don't know of any other dashboard that actually explains the numbers. Second, we will keep it from being such a dashboard, by closely listening to our users.