How to jump-start your data-driven business strategy

Have you ever looked at one of the big golfers playing in a major tournament? When they are on a green ready to putt, they will look at the green from all angles, from behind the hole, from where the ball is lying, and from the side. They do this to determine the slope and which way their ball will curve once the putt is hit. And it is understandable why they do it, because often whether a putt falls or stays out can mean a difference of thousands of dollars in winnings.

What they are actually doing, is using all the information or data available on that green to make a decision. You won't likely see them making an impulsive putt. So, isn't it time that you start reading the green in your business and make decisions based on all the available data, which ultimately means better decisions and more success?

For this you need a data-driven business strategy. Now, you have probably read about big data, data-driven processes, or data insights before, and you might even think that these are the latest buzzwords in business. Thinking about it in this light would be a mistake. If you want to improve your business processes and unlock new revenue streams, it is vital that you move to a more data-driven approach. But what does it mean to be data-driven and how can you get started? Let’s take a look.

What does it mean to be data-driven?

Being data-driven is all about using data analysis, data visualisation, and business intelligence to gain a better understanding of your business, and in the process, make better business decisions. Or, in other terms, being data-driven is the process of using data to inform your decision-making process and validate a specific course of action before committing to it. So, just like the golfer, being data-driven lets you look at all the information and evidence before making business decisions.

It goes much further than just business decisions, though, and by using data-driven insights you will become more proactive to identify new business opportunities, and you will be more agile and adapt to changing trends faster. This means, in the long run, you will achieve greater success.

With that in mind, let's look at some of the steps you can follow to get started on making data driven decisions.

How you can jump start your data-driven business strategy

The immediate question that arises is probably how you can get started with a data-driven business strategy. Luckily, there is a simple way and if you follow the steps you will be well on your way to developing a comprehensive data-driven business strategy later on. The key, however, is to start slow and not try a full digital transformation of your business all at once.

Define Clear Objectives

Before you use a data-driven approach in your business, you will have to decide what you want to do with this data. In other words, you will have to look at what your business goals and objectives are, and what it is you want to improve.

Here, for example, you will use goals like increasing the sales of a specific product by a certain percentage, or even something simpler like increasing the number of visitors to your website. Irrespective of what your goals are, the vital part is that you have one (or more) and you set it clearly. Depending on the goal, it might be helpful here to have some key performance indicators (KPI) so that you have a clear indication of where you are and where you need to go

Find and process the data

The next step is to find the data you will use to make your decision. Keep in mind that you don't need huge amounts of data at this stage, because this will only make it harder to gain valuable insights from it. What is more important, is that this data is relevant.

So, for example, if your goal is to sell more of a certain product, you might need the data relating to the product's sales figures, what percentage of your total sales does the product constitutes, where most of the product is sold, and how sales compare to your other products. You could also look for data in things like your marketing automation platform, your CRM, or other technology platforms you use in the sales and marketing processes of your business. Keep in mind, though, these are just some of the things you could look at, and there may be many more, like for example competitor and market analysis reports or channel data.

When you have the data you need, you have to process the data. This is simply because raw data is often unusable, and it should be cleaned before data analytics will have any measurable benefits. It is here that data management and data processing play a crucial role and helps you build a high-quality dataset that you can use for your decision.

Analyse relevant data

Once you have processed the data, you are ready to analyse it. Here, the aim is to spot patterns and trends in the data that will allow you to draw insights from it. In other words, let the data give you the answers. Data analytics and data visualisation tools can be extremely helpful here in giving you the answers you need.

If we go back to our example, the data might show that your product is hopelessly overpriced in the marketplace compared to your other products and compared to your competitors. This may not be good news at the time, but it gives you actionable insights to solve the problem. If you have incorporated KPIs into your process, it is here where they will play a role in showing you what the problem is and where do you need to improve.

Put together your action plan

When you have the results of your analysis, your KPIs, and a good idea of where you need to improve, you can get started with your plan to make the necessary improvements. For example, if you would like more visitors on your website, but your SEO isn't optimised, then your plan will be based around optimising your SEO strategy. Likewise, if we go back to the sales example, your data analysis might show that you have marketed to the wrong demographic. In this instance, your action plan will be based around improving your target marketing efforts. Irrespective of what the analysis shows and what your solution is, the data has driven you to make informed business decisions, and that is the essence of having a data-driven strategy.

Measure your success and repeat

OK, so you have set your objectives, gathered the data, analysed it, and made certain decisions based on it to improve outcomes. But it doesn't stop there. You will have to constantly test your outcomes based on the changes you make as a result of the data. In other words, if your plan is based on optimising aspects of your marketing strategy, you could go through the same exercise again after you have made some improvements to see what effect they had. From there you can make further improvements, or you may even learn of something new that can be improved.

Final thoughts

Hopefully, this guide was helpful and showed you how data can make a difference in your decision-making process. But as we’ve said, start small, start slow, and you will be on the path to success. For example, maybe start with one product or one part of your overall marketing strategy and see how data-driven decisions can improve that. From there you can move on to bigger and better things.   

If you would like to find out more about how our Data & Analytics experts could help you jump-start your data-driven strategy, email us at Salesforce@coforge.com

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Data & Analytics round-up February 2021

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Key Takeaways

• A data-driven strategy empowers businesses to make decisions based on evidence rather than intuition.
• Being data-driven improves agility, helps identify new opportunities, and supports proactive decision-making.
• A successful data-driven strategy starts small—focus on manageable goals before scaling to full digital transformation.
• Clear objectives, relevant data, proper processing, and iterative testing form the foundation of effective data-driven decision-making.
• KPIs play a vital role in tracking progress and identifying areas for improvement.
• Repeating the analysis cycle ensures continuous optimization and long-term success.

Why This Matters

Data-driven strategies reduce guesswork, improve decision accuracy, and enable companies to adapt faster to market changes. Starting small and scaling thoughtfully leads to sustainable transformation and measurable business impact.

Frequently Asked Questions (FAQ)

Q1. What does it mean for a business to be data-driven?
It means using data analysis, visualization, and insights to guide decisions instead of relying solely on intuition or traditional practices.

Q2. How do I start building a data-driven strategy?
Begin by defining clear goals, collecting relevant data, processing and cleaning it, analyzing it for patterns, and creating an informed action plan.

Q3. Do I need large amounts of data to get started?
No. Small, relevant datasets are more valuable than large, unfocused ones—especially in early stages.

Q4. What tools can help in analyzing the data?
Data visualization and analytics tools can reveal trends, patterns, and insights quickly and clearly.

Q5. How often should I repeat the analysis process?
Regularly. A data-driven strategy is iterative—measure outcomes, refine approaches, and repeat to improve results continuously.

4. Glossary of Terms

Data-Driven Strategy
An approach that uses data insights to guide decisions and validate actions.

KPI (Key Performance Indicator)
A measurable value used to track progress toward business objectives.

Data Processing
The cleaning and organizing of raw data to make it suitable for analysis.

Data Visualization
The presentation of data in charts, graphs, or dashboards to make insights more understandable.

Action Plan
A structured set of steps designed to address insights uncovered during analysis.

5. Best Practices for Jump-Starting a Data-Driven Strategy

• Start with a single goal or business area to avoid overwhelming complexity.
• Prioritize relevant data over large volumes of data.
• Clean and prepare data before attempting analysis.
• Incorporate KPIs early to measure progress.
• Use visualizations to uncover insights quickly and clearly.
• Allow data—not assumptions—to guide decisions.
• Revisit the strategy regularly and refine based on new learnings.

6. Common Pitfalls & How to Avoid Them

Pitfall: Trying to transform the entire business at once
Solution: Begin with one area or product and expand gradually.

Pitfall: Collecting too much irrelevant data
Solution: Focus only on data aligned with your defined objective.

Pitfall: Neglecting data cleaning
Solution: Always ensure data is accurate and usable before analyzing it.

Pitfall: Ignoring KPIs
Solution: Build KPIs into your strategy from the beginning.

Pitfall: One-time analysis with no follow-up
Solution: Continuously test, measure, refine, and repeat.

The Data-Driven Decision Cycle

1. Define Objectives

Identify exactly what you want to improve or understand.

2. Gather Data

Choose only the most relevant and meaningful data points.

3. Process & Clean Data

Eliminate errors and inconsistencies for accurate insights.

4. Analyze Data

Use patterns and trends to draw actionable conclusions.

5. Develop an Action Plan

Transform insights into concrete steps.

6. Measure & Repeat

Revisit the process to ensure continuous improvement.