Este término reside en el principio de sinergias entre datos, desde la cualificación hasta la activación, navegando por un mar de diferentes tecnologías.
El pilar clave de todo este entorno es la visión única de consumidor con datos que puedan obtenerse tanto del comportamiento (páginas vistas, urls visitadas), la información de activaciones de campañas publicitarias programáticas (interacciones con la publicidad), las plataformas e-commerce y sistemas transaccionales (productos adquiridos, búsquedas realizadas, valores de compra), CRM y “data offline” (información sociodemográfica, datos sociales), o sistemas con el consentimiento del GDPR, Muchos tipos de datos pero también muchas oportunidades para el ámbito de la personalización y la targetización de mensajes a través de todos los medios y canales pero también, un conocimiento exhaustivo del customer journey y posibles atribuciones del valor en diferentes puntos de contacto. Y todo gracias la combinación de diferentes tecnologías utilizando como denominador común el “data” (DMP, CRM, Plataformas de e-commerce, sistemas de email marketing, plataformas avanzadas de analítica web)
Por profundizar en estas oportunidades y en concreto en el ámbito de la personalización de mensajes en todos los canales, el enriquecimiento de “third party data” con datos precisos permitirá una targetización y una re targetización mucho más granular. Las marcas podrán crear audiencias basadas en datos recogidos en su tienda de e-commerce, tanto de productos que adquieren sus clientes como de productos buscados, y poder activarlo a través de cualquier plataforma de compra programática y conseguir los criterios adecuados para sus campañas publicitarias.
Más aún, los profesionales del marketing y la publicidad podrán crear experiencias contextuales y personalizadas. Con informes más avanzados y mejorados sobre atribución y de cómo los consumidores interactúan con sus marcas, estos profesionales podrán hacer foco en los puntos de contacto más relevantes de ese “user journey” y minimizar las inversiones en aquellos puntos de contacto menos eficientes. Se podrá de manera automática eliminar a determinadas personas del “funnel” de compra en el momento que se salgan de un segmento de audiencia o después de una conversión. Todo para buscar maximizar el retorno en la inversión. Y aunque suene futurista, todas estas tecnologías acabarán sacando el máximo potencial de la inteligencia artificial y el “machine learning” dado que los algoritmos sobre los que se construyen estos conceptos, fueron creados para apoyar y optimizar los procesos de decisión.
Todos los actores en la cadena de valor tendrán que invertir en recursos con los skills correctos adquiriendo talento que entienda toda la logística alrededor de las tecnologías programáticas combinadas con conocimiento de data y analítica pero, priorizando principalmente el comportamiento del consumidor. Tendrán que también confiar más en todos sus modelos analíticos, que será la única manera de hacer que todo este ecosistema “madtech” funcione, impulsando cada vez mas la analítica basada en el consumidor y personas y no la antigua basada en cookies o dispositivos. Con esa información en tiempo real derivado de un buen modelo analítico, la industria tendrá que optimizar más los canales y los dispositivos por los que se dirige a sus consumidores asegurando que las estrategias utilizadas tienen el impacto deseado. Y como prioridad, la capitalización del “first party data” de los consumidores para poder personalizar mensajes a la gente correcta además del contexto adecuado.
Estamos ante un cambio de paradigma de cómo las tecnologías van a rediseñar las áreas del marketing y la publicidad en todas las industrias y sin duda un reto relevante para todos los profesionales que trabajamos en estos entornos. Todos alineados, hacia un futuro en el entorno del madtech.
Why Has MadTech Emerged?
It’s no accident that, when reading articles about advertising technology, we often see the terms “AdTech” and “MarTech” placed next to each other, rather than mentioned independently as completely unrelated ideas. This is because the components of one may be of little use for the modern marketer without the other.
Today, AdTech platforms are not just tools used to increase brand awareness and acquire customers. Conversely, MarTech platforms like CRMs are increasingly gaining capabilities beyond passive databases of customers, and are now run on vast amounts of data, offering social media integration, artificial intelligence, holistic profiling, and much more. This alone makes the distinction difficult.
Importantly, while the term may not sound familiar to all, MadTech is not a completely novel concept.
Within the AdTech landscape, MadTech-specific platforms have existed for some time now, and a prime example of that is the existence of data-management platforms (DMPs).
As data is the key component in both advertising and marketing campaigns, DMPs combine capabilities inherent in MarTech and AdTech, which positions the platforms in between the two realms.
For advertisers, a DMP allows them to reach new audiences (via look-alike modeling) and improve media-buying decisions during real-time bidding (RTB), whereas for marketers, a DMP enables them to craft and deliver personalized communications and offers to existing and prospective customers.
What Are the Components of MadTech?
MadTech, as its name would suggest, sits between MarTech and AdTech, and encompasses elements of marketing, advertising, and technology. To understand what MadTech is, we must grasp the role of advertising and marketing technology in the digital space.
Advertising
Advertising often involves communicating to “unknown” audiences—people who have not yet become fully aware of your products and their advantages. While you may not have detailed information about potential customers, you can still target specific audiences who are actively seeking your services or who have briefly interacted with your brand (via retargeting, for example).
However, in a post-GDPR era, collecting and using personal data, including email addresses, cookies, device IDs, and location data, is a lot harder due to the rules regarding user consent.
Advertising technology includes a number of specific technology platforms:
Demand-side platforms (DSPs) allow media buyers to run advertising campaigns and buy inventory from publishers on an impression-by-impression basis via various ad exchanges and supply-side platforms through one user interface. DSPs are a key component of the real-time bidding process, and often use data from DMPs and data brokers to optimize campaign performance—e.g. increase or decrease the bid price based on information present in the bid request.
Supply-side platforms (SSPs) help publishers sell their inventory to advertisers via a number of different ad exchanges in an automated and efficient way. Even though publishers don’t need to use an SSP to sell their inventory on the ad exchange, the technology used with SSPs provides many benefits that allow them to receive the most yield from their inventory and gain clearer insights into their audience.
An ad exchange is a platform that facilitates the buying and selling of impressions between advertisers who place their offers via DSPs and publishers who put their inventory up for sale. The process is reminiscent of stock exchanges which manage the buying and selling of stock between investors and companies.
An ad network takes a publisher’s remnant (unsold) inventory, packages it up, and offers it to advertisers on a cost-per mille (CPM) basis. Ad networks have evolved over the years and now manage premium inventory across many different verticals (e.g. automotive, travel, and finance).
An ad server is a web-based technology platform responsible for storing creatives (aka ads), making decisions about which ads to show on a website, serving them, and collecting and reporting the data (such as impressions, clicks, etc.). Ad servers are to ads what WordPress is to content.
Marketing
Traditionally, marketing is more about nurturing and communicating to known audiences. It allows marketers to create, run, and manage online marketing campaigns and conduct onsite marketing—e.g. email marketing, social-media management, A/B testing, personalization, user-feedback surveys, web analytics, etc.
Marketing technology includes the following platforms:
Web-analytics tools analyze data collected by a website or mobile app and are typically used to improve the user experience of a website, measure the performance of marketing activities, and discover how users interact with a website. These tools can include traditional platforms like Piwik PRO, or ones like Hotjar that provide different features like heat maps.
A customer relationship management (CRM) platform stores and manages a company’s interactions that they’ve had with current and potential customers. Often, a CRM will include data from various other MarTech tools, such as web analytics.
A customer-data platform (CDP) is similar to a DMP, but typically collects and stores first-party data from various MarTech platforms. With the use of a CDP, marketers can manage all their data in one place, create audiences from it, and utilize it in their marketing activities.
Social-media-management platforms like Hootsuite, Sprout Social, and Buffer allow marketers to create, schedule, and measure their social media posts and activities. Influencer marketing tools, such as TapFusion and Webfluential, as well as social-media-listening tools like Reputology and Hootsuite Insights also fall under this category.
SEO and content-optimization tools enable marketers to improve their ranking position on search engines like Google and Bing.
Personalization tools, also known as customization engines, tailor the messages of a website to match the needs and interests of individual users based on information known about them.
Search-engine marketing (SEM) platforms assist in the promotion of websites to ensure good visibility in paid search-engine results pages (SERPs).
MadTech and the Benefits of Technological Convergence
No matter which technological platform we’re considering, each involves aggregating and processing vast amounts of data.
MadTech has recently started to gain traction in response to the needs of modern marketers, and helps to combine advertising and marketing technology into one seamless category.
The result is richer data, a foundation for the most complete channel for marketers. MadTech uses programs and algorithms to target audiences with much more precision than traditional marketing and advertising (AdTech and MarTech, respectively). Thanks to this, marketers can better understand exactly what their consumers want and need by using data and technology to gain valuable insights.
The convergence of the technologies results in a number of benefits for modern marketers.
Better Insights and Streamlined Media Buying With Connection
Connection takes customer data that has been collected from a variety of places—point of sale (POS), loyalty-program interactions, e-commerce platforms, and in-store and social media interactions—combines it and takes action through digital advertising.
Informing media buys with deep customer insights helps brands get the most out of their advertising dollars. It enables marketers to establish emotional connections with customers because they can identify and engage with them at a more granular level. It’s a major step forward in a customer-engagement strategy, made possible by converged marketing and advertising technology.
It’s also worth pointing out that in this post-GDPR world where third-party data is harder to come by, using first-party data for online advertising will deliver better targeting and create a consistent user experience across devices and channels (provided the proper consent has been obtained).
Elimination of Data Silos
MarTech and AdTech are equally propelled by data. MadTech offers de-siloing and connection of a number of data sets—for example, a brand’s existing customer (first-party) data from various MarTech platforms combined with advertising-interaction data from online and offline channels, as well as third-party data.
By combining this data together and creating audiences, companies and brands can perform people-based marketing, which revolves around targeting and measuring campaigns at an individual level across any addressable channel.
In addition to a comprehensive view of the customer and more precise targeting, connected customer data also allows marketers and advertisers to better assess and measure their ad inventory, media buys, and outreach programs. Better metrics lead to more effective campaigns, which, in turn, lead to customer acquisition and revenue growth.
As evidenced above, the benefits of MadTech work two ways. Marketers have more complete insights about existing customers, and conversely, because they better know their existing customers, they can streamline targeting to new, potential customers. This reduces the cost of advertising efforts.
Conclusion
MadTech is not just another fancy term coined to further litter the overpopulated AdTech nomenclature—far from it.
MadTech only emerged to give a proper handle to tendencies that have naturally evolved for years and are increasingly common in the industry, such as the ever-increasing reliance on data and interconnectedness of marketing platforms. MadTech is not an invention; it is a mere observation of the natural evolution of marketing and its indispensable connection with advertising.
