Exploring AdTech and MarTech – leveraging the best of both worlds
I spend most of my time in the wonderful universe of MarTech (covering also Commerce) but much less in dealing with AdTech. For a while I have had the feeling that these were increasingly becoming two very diverse ‘camps’ in the marketing world and there was very little constructive dialogue between the two. To address this, yesterday I sat down with the wonderful Rachel Powney to get deeper into the realm of AdTech to try and understand how that aligned with MarTech.
Apart from being better informed generally (thanks Rachael) I also felt like there were some unexplored opportunities in the grey area between AdTech and MarTech. There are lots of articles on the web about “What is the difference between…?”, but I want to dig a bit deeper into what the similarities are as I think some of the vendors on both sides of the fence may be missing a trick.
Very quickly though, just to establish a baseline:
AdTech (Advertising Technology): Fundamentally, advertising is the strategic placement of adverts in locations where your audience (ideal personas) is most likely to see them and hopefully react. ‘AdTech’ is a term that has come about to describe the programmatic management of the delivery of these messages from the Brand (This is demand side - often advertising agencies) to the consumer (This is supply side - often represented by the publishers). A huge range of platforms have sprung up to optimise and measure that process (not to mention a whole swathe of systems to manage rights, trust, security, consent, quality, etc.). Essentially though AdTech deals with consumers that are not on the brands own platforms or in their databases.
MarTech (Marketing Technology): The realm of MarTech is about the systems and platforms that you, as a brand or company, control yourself. This can be as simple as a Wix website. At an enterprise level will almost certainly be a more complex range of systems to support user journeys once the visitor enters your own ecosystem - and that can be any touch point in an omnichannel universe that you control.
And that’s the key, really – AdTech brings customers to your world, MarTech deals with them once they’ve entered it.
So, if you look at the simple customer passage from the unknown John/Jane Doe on the street to a valued VIP customer AdTech and MarTech, together, have an extremely important role to play. Why, when both these technologies are so important in customer acquisition, are they so disparate – both in terms of the technologies and the people that manage them? Also, there are some things that AdTech is extremely good at, natively, such as presenting the right Ad content to a visitor in real time, that could benefit MarTech (more on personalisation later). And, of course, vice versa.
Just a quick note on data: AdTech relies very much on customer data in the public domain. While there are a few ‘walled gardens’ (Facebook, Google) essentially it is third party data (declared, inferred and observed*) which drives the decisioning that is done in advertising, and this is pretty open. First party data from the client can be used, but for a long time this has been under-utilised in AdTech, however, with third party cookies on the way out it is forcing brands and publishers to think more strategically about collecting, storing and applying first party data.
In MarTech, data is mainly first-party and collected from the source, the visitor. It’s usually higher quality than second- or third-party data, so it's great for understanding your audience, personalisation, trends and traits, etc. and is owned by you, the company. (I’m not going to go into data privacy, GDPR etc. here – that’s another post)
So, how can these technologies work better together?
At a high level there are some strengths in both areas where a better understanding of the overlap, and perhaps a technology to bridge the gap could be of use. This is my take, but I’m sure there are more:
The value of real estate
An essential part of the media buying process is understanding where you advert is going to go. To that end, in AdTech, the bidding process, and the cost of an ad on a site will depend on the ‘ad slot’ – i.e. where is it delivered on the site; header, left hand column, in line, in the footer, a pop-up, above the fold, below the fold etc. Similarly, MarTech Marketers will pore for hours over results from software like Hotjar or Mouseflow or run eye-tracking studies, to understand the use of their own content on a website and the optimal position of teasers, buttons and promotions.
These are parallel concepts and the fundamental learnings from these two areas don’t seem to have an overlap, in fact sites that combines advertising and their own content often look cluttered and difficult to read (see the UK Daily Mail!)
A side note here: the AI around aligning internal (your own) content and ad-content is getting better, which creates more relevance for visitors. Contextual advertising and ‘signals’ are a huge topic in AdTech (more about that here). This requires even more diligence around the need to manage the co-positioning of content between the platforms.
Personalisation of content
Most good marketers are trying to push the personalisation of their own content on their website/app/kiosk and there are some good systems (either CMS, or dedicated personalisation technologies) to help them do that. But it’s often clunky and not well managed. AdTech has, for a long time, had the ability, in milliseconds to serve visitor-relevant content. They don’t always get it quite right, but it is fast and supported by some really good algorithms founded now in solid AI.
In MarTech world there are three main options for personalisation: implicit, explicit and zero click**. One or a combination of these allows you to deliver dynamic content to the site, alter search results or build whole pages that are visitor-relevant.
It feels like MarTech personalisation lags behind AdTech. Not in the technology available but in the ability to implement successful personalisation strategies. There are a lot of learnings from AdTech that marketers could benefit from in the way they deliver content to their visitors. McKinsey stated in a 2021 report that getting personalisation right can add 40% to your online revenue, so this isn’t just for fun.
Omni-channel delivery of content
I am a big fan of Composable SaaS, as described by the MACH Alliance manifesto. Decoupling the context from the content of a website allows for much more dynamic delivery of content from a single source to multiple destinations: website, mobile app, in-store kiosk, terminals, kiosks, etc. Truly omni-channel. Most brands are not there yet with embracing this, but the capability is there.
Likewise, AdTech are experts in omni-channel delivery, where can you go to hide from banners, pop-ups and in-your-face promotions?
However, nothing ties the two together. Extensive MarTech analytics will tell you where content was served and who consumed it and likewise AdTech Supply Side Platforms (SSPs) will tell you where your ads were delivered and the audience. Here too, lies an opportunity to understand the full journey of a potential customer from the initial (ad) contact to the first interaction with your brand, and eventually (hopefully) the first transaction. But (and happy to take input in the comments) the analytical systems are disparate. There is very little full-picture understanding of where a customer originated from prior to their purchase, and therefore analysing ad spend and focus is virtually impossible in anything other than a trial-and-error basis.
The best opportunity: Customer Data Platforms (CDP)
CDPs are very much ‘on the rise’ in MarTech. They differ from the traditional Customer Relationship Management (CRM) as instead of storing customer data they store customer activity. Dotdigital, Twilio Segment, Sitecore CDP and Bloomreach are a few of the leaders here in enterprise. They are very good at understanding all the engagements your customer has with your brand at every touch point on your platforms. What is lacking though, is comprehensive information about what happened before their first interaction – what ads did they see, which did they respond to, and what frequency was required to get a response? However, I feel that in terms of a development opportunity, the extension of these platforms to consume better data from the AdTech platforms is probably the shortest journey to getting a complete picture of the customer lifecycle. If the Supply Side Platforms (SSPs) can also align with the CDPs this will close the loop and further increase relevance.
In summary
This is a massive topic and due to the complexity of the MarTech and AdTech worlds it is difficult to find experts who span both areas comprehensively. All good marketing is founded in an understanding of your customer and both platforms are able to present their version – which is incomplete on both sides. There is an opportunity in the area that bridges the two (some of which I’ve outlined above), to benefit from the learnings, and develop coherency between the platforms.
There are challenges which will hinder this journey: Data privacy is hugely important, but quite the road-block in many areas. Touchpoints and digital interactions will increase across all current and new channels (I haven’t even covered Commercial Television, CTV) so this model will become more complex, and the view of the customer will become even more opaque. However, big data combined with AI shrinks many of these issues and those able to manage this complexity will be the winners.
An opportunity for existing CDP vendors perhaps, or an extension of the Supply Side Platforms (SSPs) seems an obvious area where the technology could be extended to bridge.
Notes:
*
Declared data: Information knowingly provided by a user through avenues such as an online form
Inferred data: Insights about non-demographic data, such as interests and preferences gleaned from a user’s online activity
Observed data: More concrete data gathered by tracking a user’s online activity, such as product pages visited
**
Implicit personalisation: content dynamically changed based on the visitors clicks; basically matching what have they looked at with a perceived persona and serving relevant content on the fly
Explicit personalisation: with the luxury of first party data – information the visitor has provided (e.g. by logging in) content can be served that suits that person’s individual profile
Zero-click personalisation: this is based on either i) actions taken by the visitor before entering your site (search terms in google, previous sites visited) or ii) information based on their IP address – location, company, etc.
