Data-driven marketing vs. conventional marketing
Areg Kocharian
Business Operation l Digital Transformation l Data integration I Business Intelligence l Data Oriented Marketing Ecosystem Implementation
Chapter 2?
How to ignite data-driven marketing in an organization?
Albeit all the benefits of data-driven model, transforming, as well as the implementation of this methodology includes a set of very complex stages, decorated with multiple roadblocks, which has caused majority of companies to either avoiding the transformation, or ceasing the ongoing movement due to various obstacles.
Several reports and researches, indicate that only 27% of companies have succeeded to establish a data-driven functioning model, but those who have, close to all have become leaders or high performers. ?
So, the starting point can be the revealing and understanding of those firms which don’t practice data driven model, as well as comprehending the main obstacles, After all, the majority of firms have not transformed, and the answer to WHY?, should be insightful:
1.?????Initiation:
Where and how to start?
How to progress and measure?
What are the new metrics?
2.?????Causality:
-???????Overlapped activities, complicates defining cause and effect
-???????Delays between actions serving the purpose of transformation and effect on customer and business. The managements impatience poses enormous bridles. For instance, a data driven awareness campaign has not directly and immediately result in sales, but the CFO, his majesty, demands reports on the ROI.
3.?????Lack of reliable data:
As an example, B2B business firms, do not know who the end users are or how do they behave.
4.?????Infrastructure:
-???????Unorganized data bases
-???????Cost
-???????Tools to support data driven marketing (e.g., consolidated performance dashboard or a closed loop mass emailing platform)
-???????Ineffective and unclear communications among data analysts, management, executer, IT and digital officers
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5.?????Mindset
-???????Fear of precise measurement & unsolicited accountabilities
-???????Tendency to remain on marketing activity-based incentives, not result
-???????General resistance to new ideas and change
-???????Inadequate knowledge or skills
-???????The peculiar belief that metrics, kill innovations!
Bear in mind that transformation toward a data-oriented culture and data driven model will not be realized over a night. It is a long-range journey with several issues, which will require to plan with agility embedded, gearing all stakeholders with required skills and trainings, as well as tidy implementations.
Benefiting from external experts’ opinions and consulting agencies are also useful movements to accelerate the project.
Initiation problem
To highlight the impact of data driven approach for all engaged stakeholders, a simple valid data collection and generating a momentum can be a very effective move.
For instance: A pro-active action to compensate a customer for a mistake or a bad experience, followed by a measured direct impact on business and revenue, all based on a reliable collected data. In this scenario if the data was not collected, verified and stored and if the action was not measured, this corrective action was not possible, since the company would have been unaware of the dissatisfaction, in the first place.
Another example from Mark Jeffery, Author:
“As a second example, figure below is a picture of three stores of the Walgreens pharmacy chain on a map. Walgreens is a $59 billion annual revenue pharmacy company with 6,850 stores throughout the United States. This geospatial picture shows dots that are the customers and where they live and are coded by shape depending on which of the three Walgreens stores, they shop. The ‘‘diamond’’ customers shop at Store 1; the ‘‘square’’ customers, at Store 2; and the ‘‘star’’ customers, at Store 3. This pharmacy retail chain predominantly markets using flyers in newspapers. The way they pay for the marketing is by zip code, denoted by the dashed line, for example, in the picture. Mike Feldner, the marketing manager who first created these pictures, noticed something interesting: the circle on the picture is two miles in radius, and after looking at many pictures throughout the United States, he noticed that there are no dots (customers) for a store more than two miles from the store.?
He concluded that in the United States, if you live more than two miles from a pharmacy store, you probably don’t shop there. At that time, Walgreens treated each U.S. locale equally; allocating equal dollar amounts for newspaper advertising in each zip code across the United States. But the data show that if there is no store within two miles of the zip code, customers do not shop at the store. Based on these data, Walgreens ultimately stopped spending advertising dollars in all zip codes without a store within two miles of the zip code. As you might guess, the impact to sales revenues was exactly zero. The impact to marketing, however, was a cost saving of more than $5 million, for a total cost of collecting the data and creating the plots of approximately $200,000.”
There certain solutions for each broached obstacle, which will be elaborated in upcoming chapters.?