Ingredients for building a data driven marketing organization

It’s been awhile since Clive Humbly coined the quote ‘Data is the new oil’ in 2006. In the last few years I have personally heard many C suite executives and senior marketers reiterate the need to build data driven organizations. At the outset it seems like a no brainer, why wouldn’t one take strategy, product and marketing decisions based on insights that may have handy based available data? It never fails to amaze me that ten years later, after Clive Humbly made that profound comment, there are still tons of big and small, mature and startup businesses that don’t make the investment and culture commitments needed to build a data driven organization. Tons of research and white papers exist out there that articulate the ROI and efficiency this brings to the organization. Let’s evaluate the current issues and what it takes to make some progress.

What problem are we trying to solve?

1. Moving data from spreadsheets, documents, presentations to data dashboards:

Many organizations still have their data trapped in spreadsheets, presentations, emails and other rudimentary data repositories. This causes data storage, accessibility, governance, time validity and inconsistent taxonomy issues. We need at the base level a data solution that is secure, easily accessible, having a consistent taxonomy and with time relevance if not real time data.

2. Having no in-house Data Analyst/ Scientist to having dedicated in-house resources:

Reading data and looking for insights needs people with specific technical skill sets and huge amount of curiosity. The assumption that main stream marketers and corporate strategist should be able to build insights out of raw data is the biggest misconception there is. Either the analysis is handed off to agencies that could be frightfully expensive or then it’s delegated to people who may not have an inclination or skill set to build insights. You just have to invest in dedicated talent that gets data. Isn’t your corporate, product and marketing strategy decisions worth the investment?

3. Moving from rear view reviews to timely optimization:

We all have been in numerous reviews where the data comes at the end of a certain time cycle when it’s too late to make adjustments in our strategy. Even though it may impact future programs and strategy, it has very little relevance in the now. Data if not used timely has absolutely no relevance or value. This is where organizations need to make technology investments and culture changes to bring timely insights to stakeholders that have the power to make changes to their programs and strategies.

4. Need based insights to year round insights:

There seems to be a lack of appreciation and knowledge in terms of how analytics function works. Burst analytics and periodic reporting that requires frequent setup and dismantling tend to have higher infrastructure costs in terms of technology and resource time, not to mention the loss of learning from previous insights sessions. Contrary to the popular belief, a year round investment and commitment to measurement yields higher returns.

5. Structured data Versus unstructured data:

3rd Party Market research and 1st Party data has been predominantly used in making strategic decisions on strategy and marketing. The last few years have seen a significant increase in unstructured data, thanks to social media, penetration of smart phones and proliferation of user generated content. The research industry has also seen a lot of disruption because of many exit polls and research insights going wrong. People aren’t that honest and straightforward in their answers to traditional research. In contrast, their social feeds provide a level of authentic data in terms of their behavior and likes and dislikes Hence we need overlay both these data sets (structured and unstructured) before we make any important decisions.

6. Moving from Vanity Metrics to Attribution:

Measuring revenue attribution from sales and marketing is still a big unsolved problem in many organizations.  Again, it’s mostly lack of technology investments and lack of commitment to culture change that is the issue here. It’s very easy to fall back on vanity metrics that don’t give any specific insights on the effectiveness of resources spent. The biggest differentiator for digital is the ability to measure, not able to answer attribution questions is getting into a downward spiral of diminishing marketing investments.

Data Driven Marketing Process and Essential Building Blocks


  1. Data Curation: This is the phase where you need to work on a common data taxonomy and make sure that the right plumbing is done so that data from all your sources are brought into one place and stitched together. This is the most important phase of data enablement that requires software and IT resources, because if the data is bad, no amount of dashboard sophistication and Insights skillset can solve the problem. Garbage in, garbage out.
  2. Data Visualization: There are a lot of software solution stacks that can be used as visualization aggregators for data. The data source plugins need the right kind of logic and refresh rate for this layer to be effective.
  3. Data Insights: Many organizations make the mistake of ending their data’s journey at visualization. You truly need specialists who understand how to pull insights from even refined data. Sales and marketing program managers are not equipped to build unbiased and refined insights. You could outsource this to a specialist agency, but that can be expensive and may not work in terms of providing timely insights.
  4. Taking Action: Proper workflows need to be designed so that Insights flow seamlessly and in a timely fashion to the respective stakeholders so that they can take action. There also needs to be a feedback loop where the insights team knows what action has been taken for further iteration or record keeping.
  5. Measuring value: Insights as an organization should never be run as a cost center but a profit center. Attribution workflows in the previous step are important so that efficiencies or value added can be calculated in terms actual savings or insight value given to the organization. The Insights organization should aim to break even in the first 3 to 6 months of their operation and over a period of time should return 5X value on the investment for it to be a sustainable investment that the organization continues.