Welcome to the explanation page for Qudo
We are launching Qudo, a SaaS tool where users can find market research data, insights and pre-made segments on consumers for several industries.
Users can also pick one or more of the pre-made segments, and upload them as audiences onto Meta Ads and Google Ads, directly matching all the criteria that identify the pre-made segments.
Qudo is based on zero-party data we produce via sophisticated top-level market research, which is one of our specialities. The other is data science, which we use to analyse that data using internally developed algorithms.
Users on Qudo can see the data as a series of charts, top-line insights we extracted from it, and the pre-made segments that emerged from the data analysis. Users can choose the segments they believe are ideal for their case, and upload them as audiences. That’s all they can do on the platform at the moment. They cannot upload their own data for analysis. They cannot connect 1st party data sources, or 3rd-party data. It’s all our own Qudo data. They can’t add new segments to Qudo, nor create personas “on” the tool. What they can do is use the data as they see fit, including for persona workshops in their companies. But that’s not something they do “inside” Qudo.
We are still in closed beta, but our tests have shown that if you use Qudo’s audiences, your ROAS is better than without. Thus far we have only run two tests with an Austrian bank, and they saw an x3 increase in final conversions compared to the control campaign. That was on Meta Ads. We haven’t tested Google Ads yet.
Our Research team design the studies we want to run. For example “Financial behaviour in the UK”. They write hundreds of questions, using all the best practices in market research. They deliver the research through more than 300 panels which we then aggregate. That removes pre-selection bias. We do not collect any personal information, only what people reply to the questions in the study. They cover all sides of “financial stuff” like financial needs, borrowing, fintech, etc… but they also include lifestyle, media consumption habits, psychometrics, etc… The Research team defines checks to make sure the results match our high standards. We also refresh each study every Quarter, which evolves the results but it also provides more samples to the same algorithm, making segmentation better and better.
Our data science team has coded a series of algorithms that ingest all the output from the research and analyses it to spot patterns. They employed several models, and some custom weighting. They first identify which “areas” of pertinence they find, producing the Segmentations, which they then come with segments. For example, it might spit out that when it comes to considering “Financial Needs” there are six segments: Debt Fighters, Retail Investors, Spend Thrifts, Home-focused savers, Realty Aspirers, and Vacation Vixens. That’s just 1 example. The Data Science team uses similar checks for their algorithms. They analyse outputs and variances, to make sure the output we use is correct and actionable. Otherwise, it would be pretty useless. When there are no targetable criteria, which doesn’t always happen because most segments have several criteria we can use, but when that happens, we tell the user that a specific segment cannot be reliably targeted online. Which we believe is an important piece of knowledge to have: they can target them on TV, print, or other media. Not every segment is reachable online, and knowing which one is just as valuable to marketing teams than the criteria themselves.
We then load all that data onto Qudo. We mapped all the possible answers to whatever corresponding targeting criteria we can find on Meta Ads and Google Ads. The same trait might be available on one platform and not on the other. We map ALL of the ones we can match. Some answers are just not targetable (e.g., there is no targeting on Meta for “people who are confident about saving more in the future”).
By doing that, we have a table we can look up when we put together the list of criteria that represent a Segment. So, when users are on Qudo, they browse the segments, and when they find one they want to “activate”, they can just click on “Upload”. Then the user will see on Qudo a final page with all the preselected criteria for the segment they choose. When they confirm, Qudo connects to Meta or Google and creates a custom audience on their accounts.
We have opened the possibility of signing up for a waiting list to get access to Qudo close beta. We need to onboard beta testers and run some actual real-life tests.