Understanding Analytics and Adopting a Data Driven Mindset

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You might have heard the term “big data” and “data-driven approach.” The basic concept
revolves around the idea of scrolling through, arranging and analyzing large chunks of different types of data to make meaningful conclusions, such as understanding consumer behavior and predicting future actions of human beings.

While the concept may not be as familiar to a certain business, for example, a small retail store, the use of a data-driven approach forms an essential part of most businesses today.

If implemented adequately, the data-driven approach may be the most critical success factor for businesses that rely primarily on online presence, especially websites and social media platforms. In fact, most experts argue that this approach is no longer an option but a necessity and an integral part of overall business operations.

Understanding Data

Let’s discusses some background here. It is a well-known fact and various studies have proven that most websites’ conversion rate lies somewhere between 1-3% (with an average of just 2%). So, what about the remaining 98% of web visitors? It should never come as a natural choice to neglect such a gigantic chunk of visitors as even converting 2% of the remaining 98% of visitors into customers could double sales for most businesses. The issue lies in finding the right direction to approach these visitors.

With all privacy laws and limitations, it is not usually possible to gain valuable data about these visitors. For example, you cannot simply find the address and email id of a random visitor in order to send an e-mail or a postcard to persuade them to buy your product. BUT the good news is that a lot can be done by analyzing the behavior and preferences of website visitors.

With the right set of tools, a lot of valuable data can be gathered and, later, converted into meaningful information. Analytics may involve various fields at its core. It makes use of modern IT tools, statistics, mathematics and predictive models to help website and social media managers to understand how their visitors behaved in past and what actions they may (or may not) take in the future. It may seem difficult and hectic initially but it’s all about implementing the right set of tools and approach, and most importantly the right mindset.

The applications of data analytics are immense. But, as a business or web manager,
you cannot expect to just order an over-the-counter tool to fulfill all your data needs. It may work for short term or for a very specific set of data, but you need to have the right kind of data-driven mindset in order to gain fruits in the long run.

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Developing a Data-Driven Mindset

Developing a data-driven mindset and implementing it in the whole organization may not be an easy task if it is relatively a new thing for you and/or your organization. But it is surely worth the effort as it may ultimately go on to define your long-term success (or otherwise, if you fail to implement it). While a lot can be written in this regard, we have provided for you a brief set of steps and points that, if followed, can play a vital role in ensuring a smooth transition from a rigid organization into a data-driven modern organization.

Step 1: Start with a Commitment

If you really want your organization to have a data-driven mindset, it should be reflected in every strategy you make and every decision you take. Everyone from top executives to operational staff should be well aware of the change in mindset. Moreover, a clear set of instructions, expectations, and responsibilities should be defined and implemented. Develop a mechanism of accountability and inform everyone about the benefits and importance of making a radical shift towards a data-driven mindset.

Step 2: Procure the Resources

If it is a very small business or website, you might want to learn the basics yourself or outsource most of the work. If you are part of a big organization, however, you might want to work on the required set of tools and skills and make efforts to procure the necessary resources, including IT equipment, software tools, and human resources.

Remember that you might need to set aside a considerable budget in order to ensure a smooth shift. Be very clear about the investment of the time and resources towards this mindset and the likely benefits that you expect to derive as a result.

Step 3: Data Quality / Health Audit

One of the earliest practical things to do is to ensure you have a system of auditing and checking the quality and health of data. You can start by performing an audit of existing data and then improving the overall process. On the contrary, if you do not have any existing data, you can start the process of data gathering and analyzing and as you gain a certain amount of data, you can conduct the audit to ascertain its quality and health to ensure you are moving in the right direction.

Step 4: Start Sharing

Data is of no use if it is locked away. Remember that, depending upon your business and the environment you operate in, data may quickly become obsolete. Therefore, it is important to start sharing as soon as meaningful data is obtained. Data should be communicated and training in respect of using and interpreting data should be provided to all major stakeholders.

You may also want to develop protocols regarding the extent or nature of data to be shared with each individual level of stakeholder. For example, a marketing team may be interested in an in-depth analysis of certain parts of data while senior management may only be interested in summary or major indicators.

Step 5: Keep the Data Flowing and Improving

It may be a matter of trial and error. It is quite possible for an organization to be unaware of the right kind of data initially. Start by generating basic data, improvise a bit, listen to requirements of stakeholders in respect of data requirements and keep experimenting to further improve the whole process.

Step 6: Evaluate

No shift in approach is successful without having an evaluation mechanism in place. Evaluate and measure performance against pre set performance indicators. Conduct a periodic analysis to see how far you have come towards understanding your visitors and customers. Develop a correlation between different types of data, the strategies thus formed and the success rate.


Remember that data analytics and adopting a data-driven approach is as much an art as it is a science. There is no hard and fast rule to suit each business. Understand your individual requirements and formulate the whole process around those requirements. Last but not the least; do not be shy or afraid of making continuous changes in your approach until it is mastered.


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