MadTech Mastery: Why it's Meaningful for Your Business

What is MadTech and is it important to me?

Madtech has featured prominently in recent discussions on the future of marketing, as one of the major areas of opportunity for businesses to make transformational use of emerging technologies such as big data and AI. Advertising is communication with broad audiences, often unaware of or only loosely connected to your brand, whereas marketing involves communication with known audiences with whom a relationship has been established. MadTech represents the synthesis of the two – the technology-driven convergence of marketing (martech) with advertising (AdTech). Madtech offers brands the opportunity to gain a unified view of the customer throughout the marketing funnel, enabling the tracking of customer interactions on the journey from awareness or first impression, through interest, to consideration and purchase.

Data is the heart of this MadTech phenomenon. In an increasingly competitive online business environment, advertisers are seeking any advantage they can get to deploy their advertising and marketing budgets more effectively, focusing tightly on customers with high intent to purchase and close brand alignment. The growth of big data and AI in the past decade accentuates this trend by holding out the potential for large and persistent gains in the efficiency of marketing spend if used effectively. Madtech enables and facilitates this process by integrating data silos that exist within corporate CRM systems (known as first-party data) and in online advertising platforms marketing (third-party data), presenting a unified customer view and enabling AI-driven algorithms to do their work most effectively. In recent years, organisations such as global bank BBVA have started to use MadTech to drive their sales and marketing strategy.

Madtech matters, why exactly?

As we’ve discussed, by integrating first- and third-party data from across the marketing and advertising space, MadTech allows marketers to gain a precise and holistic picture of customers’ needs, desires and intent, seeing far beyond simply their own relationship with the customer. But how is this done?

Individual businesses have detailed information on how a specific user interacts with their brand – including purchasing histories, web clicks, and numerous other contact points. By contrast, large advertising platforms, such as Facebook and Google, consume enormous volumes of data by tracking online behaviour and have a detailed picture of customer preferences, likes and dislikes, and views or opinions. However, they did not possess detailed information on a customer’s pre-existing history with a brand that would ‘seal the deal’ for advertisers, and enable them to identify precisely a customer with high intent to purchase who was also a tight fit with their brand. The two datasets were separated, with no easy and convenient way to connect them in real time.

A brand with a fully integrated MadTech stack is able to track interactions with the brand’s online advertising and tie it to future online or offline interactions by individual customers. Because advertising can be personalised to the individual using sophisticated AI models, and its effectiveness is tracked on an individual level using a single view of the customer, supply can be tightly mapped with demand. For brands with a substantial online presence and capabilities, the nature of this opportunity is substantial, if not transformational. The perennial problem of advertising has been that, as the American businessman John Wanamaker observed a century ago, “half the money I spend on advertising is wasted, but the problem is, no one knows which half.” For the first time, MadTech holds out the opportunity of truly solving this problem, and unlocking huge value by allowing advertisers to know exactly how much they should pay for a given advert to a given customer in a given situation, and ‘micro-target’ customers with great accuracy using micro-segmentation techniques.

In a world sans third-party data, what then?

In recent years, and especially in the aftermath of several scandals regarding the sharing and use of personal customer data without permission, the data privacy landscape has been rapidly evolving. In particular, the trend is exemplified by the European Union’s General Data Protection Regulation (GDPR) which became effective in 2018, Apple’s 2021 decision to require explicit consent for cross-site tracking on its devices, quickly followed by Google, and Google’s own pending phase-out of third-party cookies (delayed to 2024).

The increasing focus on privacy means that the continuing synthesis of first- and third-party data faces serious challenges. A reduced ability to track users across all channels, from first contact to purchase, and freely share that data with marketers, could have noticeable implications. It could impact the ability of businesses to achieve very fine-grained customer segmentation based on a detailed analysis of prior behaviour that has become the industry standard in recent years. In the aftermath of the privacy changes at Apple mentioned above, Facebook reported it expected to take a $10bn revenue hit, due to the reduced effectiveness of digital advertising when users cannot be tracked precisely.

However, the end of third-party data will not mean the end of MadTech. For example, in the wake of Apple’s decision, advertisers reallocated their spending toward Google, since search results are a very strong indication of a user’s immediate need. And before it ends the use of cookies, Google is developing ways to track users anonymously through look-a-like modelling, with a product called Topics. This groups users into cohorts with others who demonstrate similar behaviours and interests, as measured by visits to websites, which are also categorised by topic. Using this technology, Google hopes to retain most of the benefits of micro-segmentation for advertising effectiveness and allow advertisers to continue to micro-target the most appropriate users, but without requiring individual-level identification, and so maintaining user privacy. Google claims that the first indications are that by using Topics, advertisers will see approximately 95% of the conversions per dollar spent that they currently get from cookie-based tracking.

Madtech’s Mad Uses

Madtech offers several major functional improvements over MarTech or AdTech in isolation.

1. First, it combines the aggregated data pools of AdTech with the individual identifiers of Martech. By tying the large, rich AdTech data pools with the personal data of martech, it offers unparalleled value to brands, through the ability to micro-target and personalise messages with precision.
2. Second, messages, content and the bidding process can all be handled by artificial intelligence and machine learning, using the full spectrum of data across all sources. By contrast, while AdTech in isolation involves real-time bidding based on behavioural data, it lacks the richness of personalisation derived from first-party sources such as customer journeys.
3. Finally, MadTech enables brands to deliver personalised messages across all their media, and offer a fully integrated, seamless service to the customer.

As mentioned above, MadTech also aligns naturally with the growing importance of AI and big data in marketing. The ability of companies to ingest, process and analyse even very large data sets has grown exponentially in recent years. Integrations of new data sources such as Internet of Things (IoT) devices have become very widespread. AI and machine learning technologies are most effective on very large datasets from diverse sources, and many major brands such as BBVA have become aware of the potentially game-changing benefits of AI. This in turn has led to a renewed impetus on using technology to gain unique insight and maintain a competitive edge.

Get ready for MadTech mastery

Madtech has provided firms seeking to advertise online with large and enduring gains in the efficiency of ad spending. While this does represent a breakthrough that has driven very rapid and continuous growth in the online advertising market, it is likely that the pace of change may moderate in the coming years. The recent re-prioritisation of privacy and the resulting technical changes will need time to bed in, and it is possible some advertisers will dial down spending until they are able to re-establish a proven value case for the new approach. However, MadTech as a concept has proven its worth, and whatever changes occur, it is certain to endure.