Your data will only be as good as your questions

One of the biggest challenges for companies that collect data is to know what they can achieve with it, and they do not always measure how valuable it is in decision-making.

Giving value to it is one of the main tasks of the data analyst.

How could I identify the 20% of leads that really matter for this month's sales?

Data doesn’t take value into account when processed with expensive tools, just as we can’t determine the value of data by the volume we have rather than by the questions we ask ourselves. It sounds simple, doesn’t it? In the end, we all can ask questions; however, not all of us are ready to ask the right ones.

For example, if we have a dataset containing all the sales results of the last three years (channels, campaigns, etc.), the initial question could be: how can I increase my sales? But the data alone will not be able to answer correctly, and it doesn’t mean that the dataset is of low quality or incomplete. In fact, the data will give us many answers, but just like the question, they will be ambiguous answers. For example, we could get answers like: invest more money in campaigns, increase your average ticket, improve your conversion rate, among others.

In the end, this will not give us a specific action plan. But why?

First, when we ask, we only talk about increasing sales. But, in what proportion? We don’t know. If we don’t have a goal, it will be impossible to project how much you should invest in campaigns, how much the average ticket should increase, or to what extent your conversion rate should improve.

So the main advice to formulate a question is: to identify the problem you are looking to solve and be as specific as possible. The more specific you are, the more accurate the data’s answers will be. For example, an approach that would give more valuable insights would be: If we want to increase our sales by 20%, in which channels should I focus my efforts? This way, we could think of an action plan to replicate and improve what has been done in the channels with the best performance or identify the channels that have the most significant areas of opportunity.

Final toughts

  • In the end, we can realize that all data can be bronze, silver or gold; it all depends on the questions we ask.

  • In the Zigatta team, one of the main objectives is to transform data into gold so that companies like yours can make decisions based on data that will help you achieve your business goals.

Contact us to learn more about our Data Science and Analytics Service Offering

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