Marketing as a practice has been an ever present in human history, but the concept of modern marketing as we know it came into being after the Second World War when rapid industrialization put some distance between brands/sellers and their customers. 

Rawad Mroueh, Digital Analytics Manager at Mediaplus Middle East

Prior to the industrial revolution, buyers and sellers enjoyed close contact with one another, allowing sellers to often know precisely what customers wanted. Industrialization and the development of factory production systems, as well as the introduction of new means of transportation, created a physical and psychological distance between the producer/seller and the customer. This created an urgent need to track the precise nature of consumer demand and inform the widest audience possible about the existence of goods and services – thus modern marketing was born. 

As new platforms for marketers emerged, such as the invention of the printing press, and radio and TV’s conquest of the household, opportunities increased to create relationships with customers using mass mediums. However, the real breakthrough happened in the late twentieth century and early twenty-first centuries, with the arrival and widespread penetration of the internet, whereby marketers started to have at their disposal huge amounts of consumer data from email, search engines, website, and social media. 

Data: The Opportunity and Challenges 

The exponential growth of consumer data presented a great opportunity to marketers, but it also brought new challenges. One of these challenges is that data is generated from numerous sources across multiple formats, which creates the need for a special kind of expertise to transform, combine and analyze the data, and thus came the term data mining. 

The other challenge is the growing complexity of the consumer journey, which is now more personalized and less linear than it used to be, given the wide range of options and routes available to consumers. To face this challenge, marketing data analysts need to have a deep understanding of different marketing channels and be able interpret the emotions behind consumer engagement, especially on social media platforms. Here, design thinking exercises and other group brainstorming exercises come into play making marketing analytics a collective effort rather the sole province of analytics teams.  

Analytics: A Function and a Culture 

As much as analytics is a function, it is also a culture for “growth-obsessed” organizations, where  every employee/team member is expected to adopt an organizational culture that puts data first and builds processes and optimizes practices based on data. That said, this puts additional burden on analytics teams to be data evangelists, and make data driven decision-making accessible to every member of the organization.

At Mediaplus Middle East, we have invested in building an infrastructure that instills a data culture within our internal media team and communicates the value of marketing analytics first-hand to our clients. Our approach is based on neuroscience findings that highlights the power of visual communication and positively correlates between the frequency of human interaction with information and enhanced decision-making ability.

Accordingly, we have shifted most of our reporting from static into interactive reporting in the form of highly customizable dashboards that can embody and display even the most sophisticated analytics exercises on the fly. This not only allows our media teams to optimize marketing activities while developing their analytical thinking skills, but it also gives our clients a deep and highly accessible means of evaluating marketing performance. 

Key Marketing Analytics Applications 

Each business discipline that came into being has an analytics arm. That’s why you hear terms like sales analytics, supply chain analytics, workforce analytics and so on. This fact also applies to marketing. Listed below are the most common marketing disciplines and supporting analytics exercises. 

  • Customer Relationship Management: To be able to efficiently segment existing customers, marketers reach out to data analysts to derive metrics such as Customer Lifetime Value which is an estimate of the money value each customer brings to the business. Usually highly valued customers are treated preferentially in terms of access to offers and promotions and are given loyal customers status. 
  • E-commerce Marketing: For an e-commerce site, it is very common to analyze customer journey to identify the most frequent paths to completing a purchase. The same exercise is also an opportunity to detect and fix any technical or content flaws that customers may face while browsing an e-commerce site. Another common exercise for e-retailers and retailers is market basket analysis, which unlocks product combinations frequently bought together. 
  • Advertising: The ultimate dream of advertisers is to be able to efficiently allocate marketing spend. Although, there is no flawless method that can completely fulfill that dream, Market Mix Modelling, which is a statistical analysis technique that estimates the impact of various marketing activities, can have significant positive impact on marketing ROI.
  • Social Media: Probably, there’s no other platform that generates user content as much as social media. It’s very common for marketers to analyze verbal content such as statuses, tweets, comments, reviews, etc. to uncover audience sentiments towards a brand, product, or initiative. Data analyst, using digital dictionaries and text analytics techniques can help marketing classify audience sentiment according to pre-defined criteria. Positive, negative, and neutral sentiment classification is the most commonly used criteria in sentiment analysis.

Analytics is thought to be a function for the left-brained, yet the truth is that designing analytics exercises and coming up with creative ways to communicate the underlying value is in itself an art –  one that aims to inspire decision making and fuel organizational growth.