Adela May 10, 2023
The Challenge of Predicting Campaign Performance
AI Tools are crucial for analyzing data and measuring the success of campaigns, allowing us to make adjustments accordingly. However, predicting how our campaigns will perform based on previous KPIs is the tricky part.
Most agencies have several years’ worth of historical data but lack the expertise to extract insights and build a forecasting model that could accurately predict future performance.
The Role of Artificial Intelligence in Campaign Prediction
With the uprising of Artificial Intelligence everywhere, we thought it could be a great help for all marketers to use it to build accurate predicting models based on their current data tables to show, in a very intuitive way, how their digital marketing campaign will perform in the future. And that’s how we developed our latest functionality: AI Tools.
Once developed, we wanted the feedback of the professionals that will use it most, so we turned to one of our first and most loyal customers: Andrea Atzori, director of Ambire, a boutique digital marketing agency specializing in performance channels. He told us in an interview how they are using it and all the possibilities it has.
A Common Challenge for Marketers: Predicting Results
One of the greatest challenges faced by marketers is demonstrating to their clients that their campaigns will deliver the desired results and providing data-driven answers to their client’s questions about the future of their campaigns. Or as Andrea explained to us:
“Clients come up asking us often the same question which is; if I spend this, if I continue spending that, what is it I can expect? Am I spending to the right level of investment? All those questions, they are very difficult to predict and in the past we always use a gut feel or kind of a finger in the air to say oh, I think if we spend X we’re going to get Y.
Now you guys are helping us to actually get something that is scientific based on the data and on modeling. And it’s exciting because that’s just the starting point again. But what you can do with that, potentially, you can build a lot and you can really… the sky is the limit!”
This is exactly what we wanted to achieve with our AI Tools, to keep helping our users save time and make data-driven decisions that help them improve their services.
Using AI Tools in an Intuitive Way
We tried to do it as intuitive and easy as possible so anyone can use it. And it doesn’t even have to be used with Dataslayer queries. You can do predictions based on any data table you have on your spreadsheets. The only requirements are that it has at least 6 rows of data and one column with a date format (day, monthly, or year). Once you have that, you only need to open our Google Sheets extension, click on the AI Tools button and select the date and the column you want to predict. That’s it. A new sheet will be created with your predicted data.
A Game-Changer for Ambire
The best way to feel comfortable with our AI Tools is “to play with it” as Andrea says, in order to “understand what the tool does, how it works, and what you can do with it.”. Once you know how it works and feel comfortable with it, the possibilities are infinite. For example, for Ambire it has meant a game-changing functionality:
“We use it a lot. For us, it’s really important because we can start saying. based on the current trends, we can expect that your cost potentially can go to this level, and based on that your transactions might increase. So is a tool that at this point is very useful to start conversations with the clients, and we can be more proactive with data often.”
Accuracy and Reliability of Predictions
Dataslayer AI Tools is giving marketers great negotiating and supporting arguments based on Artificial Intelligence prediction modeling, and to help you even more, it also calculates the level of accuracy the prediction has. Because it isn’t the same to predict data based on 1 month’s of data than based on a whole year of data.
The Accurate level is calculated by subtracting 100 from the weighted MAPE. MAPE means Mean Absolute Percentage Error, it’s the average absolute percentage difference between the predicted and actual values. Also, in the data prediction, Dataslayer calculates some extra values internally that are NOT shown to the user due to their complexity, but you can learn about it in our FAQ about AI tools in Dataslayer.
The Future of AI Tools in Data-Driven Decisions
Since the beginning of our tool, we have always tried to help our users pull all their historical and present data for their reports, enabling them to make well-informed decisions. Now, we have elevated our services to the next level by integrating cutting-edge AI tools that enable our users to extrapolate future trends and insights, thereby empowering them to make even more informed decisions.
But we will end with Andrea’s words, who explain it much better:
“Like I say, the problem you got is that you’re looking at past, for that Dataslayer is great, but we’re looking at the past, right? We’re looking at data that has already happened. Now the forecasting tool is actually helping us to use that to look at the future.”
