Beeler.Tech recently hosted a PubsOnly call to talk about data visualization. It might be a super busy Q4, but enough publishers are actively considering their options when it comes to data visualization partners, that a call felt warranted.
The conversation itself was focused on the pros and cons of various top level data viz solutions in the marketplace based on people's experiences. We're going to actually add some recommendations from publishers from that call to our First Impressions library. The library already has product demos of DoubleVerify and Burt which are available to publishers, but now we are also adding what publishers have to say about specific tech.
What emerged for me through the conversation is that as we all know, each publisher has their own unique requirements. This is especially true when it comes to data visualization because a number of factors about the business will ultimately drive the strategy. My thought of the best way to think about what solution might be right for your company is to think of it in terms of maturity, starting with the simplest use case all the way to where the big publishers will need to go.
If your world only consists of Google products, Google Data Studio is where you start. Why? Because it's free and Google data easily pipes into it. There is a learning curve if you don't have experience with databases, but it's a really good place to start to learn. In fact, I recommend knowing Google Data Studio because it'll help you understand what the other solutions are doing.
The world is bigger than Google Ad Manager and this is when you need to develop a strategy. To be clear, Google Data Studio is not limited only to Google products. It can ingest other sources as well and I'm sure there are publishers who are doing amazing things with Studio. We actually have a PubsOnly call with someone importing Order Management System data (FatTail) into Google Data Studio. My take however is that at some point you might be doing a LOT of work that isn't the best use of your time.
As your requirements grow, you need to track time spent on reports. Your strategy has to be to get the information needed to run the business into the hands of decision makers as quickly, efficiently and cheaply as possible. Track time spent on pulling all the data together, formatting and distributing reports. Make that "cost" known. When new data sources are added, make it known how much more time/money that is costing you.
Publishers' need for data to run their business quickly outgrow their internal resources to keep up with the demand. The organization needs you to help them understand if they need to automate, delegate (outsource) or hire specialists. All of that starts with tracking time spent. For people who have the potential to do more than be order takers, report work is a waste of their time and potential.
Automation vs outsourcing. It's easy to assume that automation is always the answer. That's not true. There is no doubt that more and more of reporting related tasks can be automated. However, while you are working through your requirements and strategy, outsourcing can be a real good stop gap. In fact, many of the largest publishers in the world continue to outsource many report-related tasks. Things change and sometimes outsourcing solutions can react quicker than a technical one. Both automation and outsourcing solutions need to be measured by cost and actual time saved.
Have you got the point yet that you should be tracking your time?
Ad tech data is very specific to ad tech. Get a solution focused on it (for now). Now, there are those intrepid souls that will want to build their own solutions and there are amazing tools out there with which to do that. Godspeed. Ultimately non-ad tech specific solutions may be on your path. I'll touch on that later. My only thought is that the Burts, DoubleVerifys and STAQs of the world have been focused on aggregating this data for clients for years. They are better positioned when a data source changes or breaks. Data sources will change and they will break.
It's at this point where you are going to want to hear from publishers like yourself and what solutions work for them. Experiences will differ, but know that someone else is further along than you on this journey. There is no shame in following in someone else's footsteps and it'll save you time. Sometimes a lot of time.
(Shameless plug - that's why we created First Impressions, so you can see the solutions and why a big focus of our Beeler.Tech slack workspace is partner recommendations). Watch the Burt First Impressions video. Watch the DoubleVerify First Impression video. We're also sponsored by NinjaCat.
Ultimately, you need a solid data aggregation strategy and solution. Do not underestimate the work that might fall on your data science or IT/development team to connect all these pipes. In fact on our PubsOnly call, some decisions were made based on the desire to not be reliant on the data science/Business Intelligence team to get the data they needed. We recommend building a bridge with these other departments as part of a larger organizational data strategy.
Data aggregation is only part of the solution. Time to visualize. This is where the major solutions start to differentiate and new players are introduced. A visualization strategy is going to be driven by who these visualizations are for. The requirements for an operations team is much different than the C-Suite in this regard. Several publishers expressed that some decisions about what solutions they settled on was driven by what management needed. One pub brought up the great point that management didn't want to have to log into multiple systems for multiple dashboards. Centralizing your visualizations may be as important as aggregating your data in one place.
To that point, if you are considering a solution, it is very important that you look beyond your department and at the organization as a whole. If the company is going to diversify their revenue streams beyond digital advertising, make sure your solution is going to accommodate that need.
This is where other players came into the discussion. A few opted to use multiple solutions: a STAQ or Ad-Juster (DoubleVerify) with a Domo or Tableau. This allowed them to get the ad tech data aggregation they needed and the visualizations the way they wanted them. I should note that one publisher was primarily using Domo – they opted to do the mappings themselves.
My recommendation in this regard is having multiple solutions (at least one to aggregate and one to visualize) might make sense if you have the budget. You need to consider if the ad tech data focused solutions can match what other solutions can do in terms of machine learning capabilities (now and in the future), flexibility, and ability to ingest lots of different kinds of data. I ask you, on this topic and others: push the vendors in our industry. Data visualization is going to continue to evolve rapidly over the next 5 to 10 years, not just in our industry but in all industries. These vendors know that. Help them shape that roadmap as a true partner.
Last thought: as I discussed with Ben Reid of Elasticiti, all companies like to say they are data-driven organizations. They are not. However, that can change. What it requires is someone (you) to start getting things aligned to get to that point. Visualize yourself making data visualization happen for your company (what a terrible pun to end on. Sorry).