Successful internet marketing companies have always relied on data to measure return on investment and help improve performance.  It is how the data is used that can help drive the success of the organization. If you are involved with your company’s internet marketing training, or if you manage a marketing department, it is important to understand the key differences between data driven and data informed marketing. 

A data driven marketing approach places significant weight on data that has been collected during the company's regular operation. This data shows where the company has been and what has worked best for them in the past. The amount of data that can be collected from web servers and hosting companies is staggering. This type of data is relatively inexpensive to collect, so there is immediate economic justification for this effort. The company may not wish to, or may not have the resources to justify the expense of more complex data collection efforts, or they may see such effort as unnecessary to their business model. Businesses that place heavy emphasis on readily available data that is easy and economical to collect are operating in a data driven mode.

Data informed marketing uses the same data, but it is not the primary factor in decision making. Other factors are taken into consideration and given equal or greater weight. Other influencers can come from a wide variety of sources, including observation of market trends, social factors, fashion, evolving customer needs, and even intuition or gut-instinct.

To help illustrate the difference between a data driven and a data informed approach, consider a company that sells apparel. Assume the company website receives significant traffic but does not seem to be engaging its visitors. Sales tend to be regular but slow and data indicates increased revenue when special events are highlighted, such as a “buy one get one free” advertisement on the home page. In both marketing models, the manager or marketing team will use the same kind of data collected from their website, but what they do with the data will demonstrate the difference.

In a data driven marketing effort, the data that shows past performance is the most significant factor when it comes to decision making. This data shows revenue goes up during special sales.  It is repeatable and it can be documented as successful every time. Management may conclude that concentrating on more sales and promotions is the best and safest way to proceed.

In a data informed marketing effort, management is encouraged to weigh current data along with other factors.  This approach may conclude that special sales, even if successful, may not lead to the increased performance they'd like to see.  Since their product is apparel, fashion trends are taken into account. What colors are losing popularity and what colors are seen as fresh and new? Intuition is also important. Could these colors be used in the user interface of the site to increase customer engagement?

Answers to these types of questions cannot be answered by current data collected from the site.  In this environment, the company decides to continue with special sales, but decides to test out some new colors in the product line, and some new styles. They may even address the issue of site penetration with A/B split testing of new colors in the website's user interface. This approach takes more time, can be more expensive and carries some inherent risk.

Both of these marketing models can result in increased performance. In data driven environments, changes often result in micro-improvements, rarely making a big impact. In comparison, the data informed environment has the potential to significantly increase sales performance since it anticipates future consumer trends and customer behavior.  Many believe that this is the most significant difference between the two marketing models.

Some companies thrive on data driven marketing and maintain profitability based upon intelligence gleaned from easily available sources. Other companies find more success using the data informed model, even though it carries a certain amount of risk. Many top marketing analysts consider the data informed model to be the best practice, since this method takes into account industry trends and other factors of a non-empirical nature that can often be just as relevant as hard data.

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