Instagram Feed

+234 7046214497 | hello[at]


Home  /  Industry Info   /  Data Driven Marketing: From OOH Compliance Monitoring to Knowledge Discovery in Databases

Data Driven Marketing: From OOH Compliance Monitoring to Knowledge Discovery in Databases

by Femi Adenekan




The advertising industry in Nigeria has grown over the years in spend and spread with advertisers churning out new campaigns to promote their brands and services on traditional media including radio, TV, print, especially Out-of-home (OOH) across the country.

The OOH industry spend increased to over N30.8 Billion in 2018, recording a 6% rise from the value in 2017 and is expected to be on the increase in 2019 being an election year where political parties dominated the industry in the first quarter.

Over time, larger brands in the Telecoms and Beer categories that budget billions on OOH advertising annually have developed the need to monitor their spend, making sure their campaign deployments are well executed on these platforms.

This challenge brought about the establishment of the media monitoring agencies who track these campaigns using improved monitoring technologies and tools such as the TMKG’s Postertrack application to provide proof of performance reports through which the various media owners get paid based on their level of compliance.

With over 11,000 standing OOH structures across the country, the growth in the Nigerian advertising industry has generated large volumes of data. Over the years, media auditing agencies such as TMKG have gathered this advertising information of the brands deploying outdoor and require their monitoring service including their competitors and the industry at large.

The questions we are asking now are: what happens to this accumulated data? How do we evolve from just providing compliance reports? What can be done with the vast amount of out-of-home advertising data collected? One sure way is to mine the data to discover insights for the industry.

Data-driven industries such as advertising are looking for new methods that will help them leverage accumulated data or “Big Data” and one of the techniques is the application of the Knowledge Discovery in Databases (KDD).

KDD, as the name describes, refers to the broad automatic extraction process of non-obvious, hidden knowledge in large volumes of data to find information through the application of particular data mining methods to identify patterns, statistics, knowledge acquisition and data visualization from databases of advertising information gathered over time.



Understanding and Defining Need to Discover OOH Knowledge

Before we can consider extracting knowledge from this vast amount of data, certain questions need to be asked based on the curiosity of experts in the OOH advertising industry. This questioning phase is the stage of identifying the need for outdoor knowledge, using business objectives and current infrastructure. Some of the questions may include:

  • Are there more boards out there?
  • Are there more brands in other categories apart from the visible ones deploying?
  • What are their advertising patterns out there?
  • What formats are being deployed?
  • Where are they being deployed?

OOH Data Collection and Preprocessing

Data Collection

TMKG deploys field auditors who survey out-of-home board using the Postertrack android application installed in GPS enabled devices in over 80 towns across Nigeria. In the process of auditing, the auditors carry out compliance and competitive monitoring by taking water-marked pictures and fill survey questions of each OOH board encountered.

Preprocessing of data involves approving or disapproving uploads; correction of inputs, removal of duplicates and supplying missing values to ensure information of each site is accurate. Following this stage is the extraction of patterns: data mining.

The data mining stage generally involves two models, the predictive model which is used to predict unknown values from known values by classification and prediction; and the Descriptive model which is used to find human-interpretable patterns that describe the data by clustering, summarization, and association.

Presentation and Evaluation of Knowledge Discovered are implemented by employing Visualization techniques to help users understand and interpret and make decisions based on what they observe usually on business intelligence dashboards such as the Postertrack web.


Presentation and Evaluation of Knowledge Discovered

Visualization may include charts such as Pie charts, Stacked bar graphs, Histograms, Time series sequences, Tree diagrams,  and Geospatial viewing on maps


Pattern evaluation provides business understanding which may lead to a generation of new business requirements that may be raised because new discoveries from information harnessed after results generated by the data mining model are evaluated against the business objectives/defined problems


How does Knowledge generated drive Agency Marketing?

Data-driven marketing has changed from an innovative tactic to an essential part of any brand’s advertising and business strategies; it refers to approaches built on insights pulled from the analysis of vast amount of data – in this case, OOH advertising data, collected through methods described above to form predictions about future advertising trends and applying that information to improve marketing efforts.

Knowledge-based marketing can empower us a media monitoring agency in our promotion strategy through:

  • Trend analyses: The delivery of industry advertising insights such as spend, presence; spread over time; advertising peak/ off-peak period also including a possible forecast future OOH advertising deployment.
  • Customer/Brand knowledge: In-depth analysis allows us to know more about current clients and their competition; identify and profile new prospects and their deployment trends to facilitate prospecting; identify leads that are likely to subscribe for audit plans such as annual retainership, one-off, or pay as you go, based on advertising trend
  • New and enhanced products and services:  Acquiring new information previously unknown from retrospective data will increase value by surrounding current out-of-home product offerings with additional and better-suited out-of-home information including detailed spend trends across brands and categories, presence information and Outsight reports.


Social Media Marketing

Social media marketing primarily covers activities involving social sharing of content, videos, and images for marketing purposes, as well as boosted social media campaigns which will lead to

  • Increased monitoring agency organisational thought/knowledge leadership online
  • Increased SEO ranking for unique content
  • Detailed information in published articles/opinion
  • A robust load of information/industry knowledge to share



Key Takeaways

  • Data is a collection of facts, such as images, words, measurements, observations or even just descriptions of things
  • Information is data in a context
  • Knowledge is  generally internalized  information, left to the interpretation of the user of information
  • Since advertising data is accumulated over time, there is a need for a process of discovering hidden patterns in the huge amount of the data which leads to a process of discovering the hidden industry knowledge
  • To discover knowledge, five processes are involved and they include, data collection from the field, processing, transformation, data mining, evaluation/interpretation
  • Knowledge discovered is used to understand the players in the outdoor industry, produce refined reports to enhance direct marketing to existing clients and new prospects offline and on social media