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How To Collect and Use Your Data In Business

Data Cloud

Collecting data is crucial if you want to keep tabs on the metrics and overall effectiveness of your business choices. Collecting and using your unique business data can lead to better decisions, help identify opportunities for improvement, and enhance your understanding of customers. Simply put, if you mine the right data, you can transform it into a resource for smart decision-making and business growth.

So let's dive into how to make the most of your data. Five steps are central in navigating this process:

  1. Pinpoint and gather your data

  2. Filter out the noise. Think of it as separating the wheat from the chaff, ensuring your data is as accurate as possible

  3. Find the hidden insights. This is where your analytical skills come into play, turning dry stats into insights

  4. Put the data to work. Weave the insights into your decision making

  5. Tell the story. Take those data-driven insights and turn them into compelling narratives that resonate with your audience

Let’s dive a little deeper.

1. Pinpoint and gather your data

Pinpointing where your data is coming from requires two types of data collection methods: automated and active. When you combine the two, you strike data collection gold.

Automated systems give you the broad strokes—important data that shows you how your business is running. Active data collection provides equally valuable, yet less obvious insights—the context of the data that tells you what the numbers cannot.

Pinpoint where to find and collect your data utilizing tools that support both automated and active data gathering for optimal results.

Automated data gathering

When it comes to data collection, two tools to lean on include customer resource management software (CRM) and enterprise resource planning (ERP) systems. The web analytics from each provides valuable data related to how customers are interacting with us and what's really going on inside our business. Think of them as background engines doing the heavy lift.

Both tools track everything from customer preferences to sales trends and keep an eye on how efficiently things are running on the inside. It's like having a dashboard that gives you the real picture of your business at a glance. These systems remove the grunt work, the guess-work, keep your database current,  and supply facts to help reinforce business decisions. No more manual data entry or trying to keep up with the constant flow of new information.

An example of automated data collection is an in-house monthly and quarterly financial report my company does for a client. We do this through a third-party reputable data connector to connect directly from Quickbooks Desktop to PowerBI. This real-time connection allows us to completely remove the need for the manual downloading of reports and transmission of data.

Another example of the benefits of collecting automated data is a project we worked on for an advertisement campaign. The advertising agency targeted an audience of both men and women 30 to 65 years old. We collected the campaign data and analyzed the results. We noticed, from the data, that 75% of advertising engagement came from women over the age of 50 and more than 60% of that from a subset of the area targeted.

The next ad campaign targeted these subgroups. The result of this new direction was a higher engagement rate which increased the client’s return on investment (ROI).

Active data gathering

Automated data collection is great, but it’s not enough to get the full picture. This is where old-fashioned active data collection factors in. Think customer surveys, feedback forms, and listening on social platforms. Active data collection offers a direct line to the customer's thoughts and feelings. You get to hear what customers are saying, in their own words.

There’s also access to informal feedback from customers and market segments through social media. Dive into the social media comments section and sift through the bots. Listen in on customer service calls, and pay attention to what people are saying in surveys. All of this is the equivalent of having a casual chat with your customers.

This active side of data collection is about collecting raw data, but it’s also about understanding the stories behind that data. Why are customers acting a certain way? What's driving the trends we see?

My company often trains clients and their employees on how to collect and interpret informal data. We teach how to pull out details related to the little things that bug their customers before they grow into something bigger and more problematic. We help them find the opportunities where they may up their game.

2. Filter out the noise

Once you have collected a large quantity of data, the next step is to filter out the noise by identifying the quality data. Take steps to validate the legitimacy of the data you’ve collected and organize the information into categories so the key insights from your data can take shape.

Validate Data

Data validation ensures the data you’ve collected is reliable, the sources trusted, and the data collection track you’ve taken was the right one. Are the numbers accurate? Did you gather data that is relevant?

This step is especially important when you’ve pulled a large quantity of data, or used multiple data sources. Structured Query Language (SQL) is a tool often used to validate data. SQL is a programming language that stores and processes information into a relational database so you can see how the data points relate to each other and begin to find common themes.

My company received a client request to investigate an issue involving duplicate pharmacy claims data and we used SQL to identify issues. The client thought the issue was limited to one client. After creating a script using SQL to identify duplication, we were able to validate that the issue was a system error, and rectified the problem before any issues escalated.

Categorize information

After validating your data, it’s time to organize it. You may have data that map to customer information, operational metrics, or financial. The key is to sort the data into categories to easily find, make sense of, and connect the data to visualization tools.

Once you’ve put your data into categories, you can use tools like Looker Studio, Tableau, or Power BI to turn the data sets into graphs, charts, and heat maps. The visual representation of your data makes it tangible and compelling.

My company used Power BI to help a client isolate and address an issue they were noticing in one of their territories. The data visualization showed the location of the outlier problem much clearer than a spreadsheet would have and our client could quickly take action and address the issue.

3. Find the hidden insights

Next, it’s time to identify the insights hidden in all of the data. Analytical frameworks are useful toward this end.

One useful framework used to analyze the data is to break it into strengths, weaknesses, opportunities, and threats (SWOT). The SWOT framework sorts key aspects of your data into its main buckets:

  • Strengths are the areas where you’re crushing it, whatever you have in this category, keep doing it

  • Weaknesses point out where you might need to up your game, maybe areas where you are receiving consistent complaints from your customers

  • Opportunities are hidden gems, waiting to be discovered and capitalized on. Maybe there’s an adjacent market to consider that would fit your business

  • Threats are the challenges you need to keep an eye on, the potential roadblocks on your path to success such as something your competitors may be doing significantly better than you, or a change in the political climate that could adversely affect how potential customers view your company

4. Put the data to work

Once you’ve found the insights hidden in your data, use them to shape and adapt your strategic planning and optimize and improve processes. Consider these next steps.

Plan strategically

Develop a plan to make the data work for you. Take the raw numbers and transform them into something that can direct your business strategy. Let's say your customer data shows a shift in preferences, for example. This is a cue to adjust your offerings to keep up with what your customers want. You can be proactive, rather than reactive, if you follow the data. Data can inform your strategy to keep pace with the preference of your target audience.

Optimize and improve

Next, look at the operational data to optimize and improve your systems and processes. Your data may show, for example, that certain tasks are taking longer than they should. The data can determine if this is a workflow issue, a tool or training issue, where the bottlenecks are, and what could be automated. Plan to make every part of your operation as efficient as possible.

Build a continuous feedback loop

Set up a continuous feedback loop to collect and use data on an ongoing basis. This will help you evolve and improve in real time, and even anticipate changes needed to stay on course or venture into new areas of business growth.

5. Tell the story

Now it’s time to tell the story the data has revealed. Business storytelling inspires and compels clients to use your business or service. Do so with persuasive narratives and by showcasing impact.

Craft persuasive narratives

Extrapolate  insights from the data into strong storytelling narratives that connect with your stakeholders. Let's say the numbers show a surge in customer satisfaction, for example. Instead of focusing on the statistics, tell the story that led to the surge—perhaps you identified and addressed a problem. All storytelling, even in  business, should entertain. Aim to inform, engage and inspire your reader with persuasive storytelling.

Showcase impact

Be sure, with every story you tell, to showcase the impact. End each story with information about the impact or results of the improvement that happened. How did things change for the better? This is where you can use case studies or before-and-after scenarios to showcase the concrete results of your work. Did, for example, a new marketing approach boost sales? Show the sales figures, if so, before and after the campaign.

Provide evidence of how data driven decisions can positively affect business outcomes. This will show stakeholders the value of data mining. It will showcase that these aren't just numbers on a page; they're indicators of real, tangible progress in your business.

Follow the data for success in business

Make better decisions, identify opportunities, and improve your customer understanding by collecting, organizing, and pulling out key insights and narratives from your data. Make data an important business tool as you improve your product or service.

If you’d like to find out more about my company OBIS and what data can unlock for your business needs, feel free to reach out. Or feel free to book a consultation if you are ready to dive right in!


This blog was written by Jacqueline Tangorra, Founder of OBIS, in partnership with UpWork.


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