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Get Busy Optimizing Your Data or...

Get Busy Optimizing Your Data or...

Note: Spending some time recently with a client, helping them sort through their data aggregation and clean-up, gave me the opportunity to catch up with Randa Minkarah, Co-Founder & President from Resonance A.I. Randa and I talked about the challenges that companies are still having regarding not only being “data-driven” but also turning their data into insights to get what they (actually) want – more revenue. Randa details below a few simple steps (and simple home truths) about this process. 

4 Ways Data Can Help Create Sustainable Revenue Growth

There is no question that year after year, the cost of revenue (COR) generation continues to climb. Look at publicly traded companies in nearly any sector and read the reported costs associated with sales and marketing. In almost every case, the costs of acquiring revenues continue to outpace the gross revenues generated. It costs more to make the same money. In today’s world of shifting digital and economic landscapes, tapping into data in real time and extruding insights gives executives a critical tool to stay ahead of the curve. Near real-time decision making is a necessity - not a luxury.

Make Data Accessible

For many companies, data is often in silos in various departments. IT doesn’t generally facilitate building a comprehensive data lake or warehouse. They are too busy keeping the basics running smoothly.
Very often it takes a c-suite leader judged on achieving revenue targets to see the value of complete data integration and accessibility. Remember – There are no silver bullets. It takes time and commitment. It means opening that data flow to allow for it to be aggregated into usable forms. Many times, it just seems too hard. Using some of the tools and services available these days, it doesn’t have to be, and it is critical to your success and survivability in this age of data-driven decision making. To quote the movie The Shawshank Redemption (more or less), “Get busy optimizing your data or get busy dying.”

Data Must Be Coherent

Granted, data from disparate sources can be hard to collect comprehensively. Don’t let that stop you. Clean data in well-defined fields that is easily accessible will give you the best results. Additionally, spend the resources needed and build an Application Programmer Interfaces (API) to allow for easy access to and from the database(s))

Conversely, there are simple to deploy solutions (software/platforms as services) that do the heavy lifting for you. Ideally, a team loads from all the company data sources relevant to revenue generation, cleans the data and harmonizes so that analysis and machine learning is now possible. Data clutter to data clarity.

Now, your company can begin to harness its proprietary information to work generating insights and sustained revenue growth. The answers to your customer’s journey, customer’s lifetime value, customers profiles and where your best opportunities lie is within your data.

Make Your Data Complete

Often companies have customer purchase data, but they don’t have enough data about their customers. They don’t have all the relevant information needed to truly derive insights. A good platform or service will integrate third party data to complete the dataset needed for modeling and generating insights.

Third party data can be proprietary, licensed or free of charge. Census data, weather data and Bureau of Labor Statistics data are examples of third party data that may be enlightening information to consider when looking for the levers that grow revenue sustainably.

Get Experts and Collaborate

Believe it or not, the easy part of data-driven revenue growth is collecting and sifting the data itself. The “hard” parts are:

  1. Defining exactly what question(s) you want to mine the data for answers to. This takes someone inside your organization who understands the goals that you want to achieve working in conjunction with a data scientist or more often a firm that specializes in this type of consulting.
  2. Finding a Data Scientist or firm to collaborate with. While there are a plethora of data visualization tools out there they are often self-help. Self-help in data analytics is the long road to success if it's not a skillset inherent in the organization.

To quote a Harvard Business Review article on this topic: “This part of the process works best when it’s a broadly collaborative one. Using statistics, reporting, and visualization tools, marketers, product managers, and data scientists work together to come up with the key insights that will generate value broadly, for specific segments of customers and, ultimately personalized insights for individual customers.

Insights need to be actionable and tailored as well as delivered to various team members that are along the entire chain of revenue acceleration. There are several firms that specialize in helping you along this path. Use them to help you make – more. Collaboration means that you only need be an expert on your own business, not a data expert to win in today’s shifting business landscape.

A good solution will deliver insights that are immediately understandable – in the language of your company – not the language of the platform.

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