In last week’s Growth Leaders virtual roundtable I had the pleasure to discuss about Ad-Tech and MarTech with 4 hyper talented and experienced industry professionals: Oren Greenberg, Emiljia Frew, Lavan Sornarajah and Fintan Gillespie.
Together we have over 60 years of experience in the industry, covering pretty much every B2C market sector and some B2B. In different capacities we have worked with Google, Apple, HSBC, Coca-cola, Uber, eBay and Snap, (on top of multiple start-ups and scale-ups).
The conversation topic spurred from a mix of curiosity and frustration, which I believe comes from the following:
1. The awareness of our dependency on ad-tech for our jobs
2. The constant need to update our knowledge in this field
3. The experience to know that tech often doesn’t work as well as it should
From our chat four key themes emerged.
There is too much MarTech out there
As online advertising and sales are areas of huge growth, with no signs of stopping, this has led to a chain reaction that looks a bit like this:
What became apparent from our conversation was also that demand for MarTech is highly fragmented. It can vary depending on company size, product value, purchase frequency, marketing strategy and sales channel (B2B vs B2C).
This fragmentation can go even further. I remember that when working agency side as Head of Performance Marketing, I used to regularly review all bid management solutions in the market for our enterprise clients. I found that different bid management algorithms were more suitable to certain verticals vs others: the impact between the right and wrong tech solution was up to +/- 30%.
This justifies the huge explosion we have seen in ad-Tech, as shown in the brilliant and infamous infographic below.
Personally I really like this table as it gives one immediate insight which is: there is too much complexity in the market for any insight to be easily gained.
Armed with this awareness and knowing the value-add of MarTech we know that for any meaningful gain to be had there will need to be significant investment in time and research.
How does one put together the perfect Tech Stack?
We all came to a quick agreement that there is no such a thing as the perfect stack, it all depends on the company’s specific needs. So clarifying what those needs are is step 1. In this case “needs” reads as: success factors. E.g. to win does a business need to excel in customer acquisition, retention or engagement?
Once that has been determined a true research process should begin, mapping out the requirements needed e.g. what does excellence look like for customer retention? This is step two and it will define the requirements, which should then be scored in order of impact.
Step three is about scanning the market: looking at secondary research online like Gartner or E-consultancy, going to conferences, finding out what competitors are using and when possible asking people you know and trust what their experience is with different solutions.
The fourth step is to meet with the most relevant providers, have an in-depth look at their technology and score them on the key requirements.
The final step is to determine the key risk factors and work out a plan to mitigate them: when possible with a test.
Not only did we find that this process is rarely carried out thoroughly, leading to the purchase of the wrong solution, but very often we have seen firms buying too much technology. Either wanting to buy the most sophisticated solution in the market, (expensive), before it’s needed, or buying multiple solutions for the same problem, (this is often seen in larger enterprises, sometimes due to political dynamics).
New trends and developments?
With so much fragmentation there will certainly be an element of consolidation coming to the market…..that’s what people will tell you, and they have been telling you that for a long time. It’s also easy to assume that Google and facebook or Amazon will take the lion share of the market, I heard that in 2011.
Those assumptions are both true and false. While there has been an element of consolidation and the likes of Google have grown the ad-tech offering, the market is also fragmenting – the chart above showing the landscape for 2019 proves it (as it’s bigger than the ones from previous years). This is because the following four trends are happening simultaneously:
- Big tech firms are aggregating
- The market is expanding at a faster pace
- Increased competition requires increased specialisation
- Machine learning is increasingly applied
The biggest online advertisers are building in-house solutions, purpose built for their needs (e.g. Amazon and Booking.com). That is a viable option only when huge scale allows for the investment. When that is not the case, but advertisers need an edge to implement their strategy, that’s where a new opportunity is born for a new MarTech solution.
Based on our shared experience we found that big tech suites, (buying tech from the same vendor), are rarely an optimal solution, but certain parts can go very well together. The instance where this tends to work well is for larger enterprises, where decreasing complexity is often a substantial value add.
Other trends we have seen are:
- DMPs being integrated with other ad-tech products (read aggregation)
- Advertisers linking directly CDPs to measurement platforms
- New patents being filed for fingerprinting-like solutions
- MMPs are moving into the measurement leveraging the data they have
What about measurement?
Measurement, tracking and analytics solutions make up a large part of MarTech. As we discussed in the previous Growth Aperitivo talk, this is another area of huge value add and complexity: this heightened by the increasing mobile nature of the internet and the rise of walled gardens. To that we must add increasing privacy concerns as a major trend.
As a result we need to embrace uncertainty if we want to be smart with measurement. Instead of using incorrectly accurate deterministic data sets, we need to move towards a probabilistic approach that embraces incrementality. At least for ad measurement.
One exciting vision for the future of this space, at the intersection of data and MarTech is one of flexibility. Ensuring a backbone of clean accessible data and build on top a flexible layer of solutions that can be tested, mixed and matched according to circumstances. This approach ensures for scalability and future-proofing.
Stay tuned for this week’s Growth Aperitivo roundup (on measurement and testing).
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