B2B companies now have access to more data than ever before. But what happens to that data, does it degrade its performance over time, or does it use it to drive business growth?

For companies that use data to drive decisions, they can gain a competitive advantage, lower business costs and increase profits. But how?

By now, each person will be generating 1.7 megabytes of new information per second. Considering that there are more than 7.7 billion people on the planet, the amount of new information generated every second is equivalent to more than 25,000 hours of videotape.

All of our digital behavior is recorded. But for many companies, this data resides in dashboards and databases and will never be used. The good news is that you can use it for business growth strategies to make better decisions without having to downgrade data to waste.

In this article, we’ll share what data-driven decision making is, how your business can benefit from using it, and include a five-step process that you can use to create smarter business decisions.

What is data-driven decision making?

Data-driven decisions are not about using what you think is the best strategy, but strategies that use data to inform business decisions.

Often referred to as DDDM or information-based decision making, you combine historical information to analyze trends and make future decisions based on past work rather than intuition, opinion, or experience.

The company that contains DDDM location data is at the heart of every decision they make.

How can you benefit from data-driven decisions?

In business, there is always an element of risk, but data-driven decisions make you less vulnerable to risky decisions going wrong.

For example, suppose you are planning a go-to-market strategy for your SaaS company. Instead of starting from scratch and hoping to adopt a new strategy, take a look at previous product feature releases. What works? Don’t implement any ineffective methods.

In short, make smarter business decisions based on the data you collect, do more of what works and less of what might not.

Research supports this model.

Leveraging big data business experienced 8-10% profit growth and 10% reduction in total costs.

If you’re still not sure, consider the following:

While 91 percent of companies say data-driven decisions are important to their business growth, only 57 percent say their business decisions are based on data.

Data-driven decisions are a great way to gain competitive advantage, increase profits and reduce costs!

What business decisions can I use the data for?

Now that you know how to benefit from data-driven decisions, the next step is to determine how your organization uses data to make decisions about how to grow your business.

For example, you can use the data to find out:

  • Finance: What’s the most cost-effective way to hire new employees, or the cheapest way to promote a new product?
  • Growth: What activities can be done to prevent loss? How to improve customer loyalty? Are planned new features likely to impact business goals?
  • Marketing and sales: Which advertising channels have the best ROI? Which sales activities generate the most leads?
  • Customer Service: What is the most cost-effective way to process support tickets? What channels can improve response time?

How do you use data to make business decisions

Before analyzing your company’s dashboard, it’s a good idea to have an action plan that details how to find the data you need and, more importantly, interpret it to make the right business decisions.

You can use the following five-step process to get started with data-driven decisions.

1. Look at your goals and prioritize them

Business goals must be at the heart of any decision made.

So first ask yourself: What goals do you want to improve?

When making a decision, start with what’s most important.

For example, suppose you want more people to subscribe to SaaS tools. In this case, generating more registrations is the main priority. However, in the study phase, it is possible to find that 75 per cent of premium subscriptions come from Beijing, but less than 10 per cent from Hangzhou or Shanghai.

Therefore, the goal is to “increase SaaS paid membership in Hangzhou and Shanghai”. Once you’re sure, you’ll need data to back it up.

2. Find and provide relevant data

Once you have identified the problem to be solved and the decisions to be made, you can find and provide the relevant data.

It’s important to emphasize that the word “relevant” is key here.

You don’t want to spend hours analyzing data that won’t have any impact on your final decision, so keep your data relevant and only collect data that is relevant to your goal.

You can find relevant data from the following sources:

  • Web analytics
  • CRM software
  • Business Intelligence platform
  • Social listening tools
  • Customer feedback

This last point is particularly important, as 60% of companies say that using customer feedback as part of their decision-making process has contributed to their most successful projects.

Going back to our SaaS subscription example, you can ask users why they buy skins and what makes them choose our product over our competitors’, insights that will help you deliver a more compelling message to users in Hangzhou and Shanghai.

Even if your goal has nothing to do with acquiring customers, such as “What can we do to prevent churn?” You can still find the data.

3. Draw conclusions from these data

Look at the historical data collected and try to identify patterns or trends.

If we use the “reduce attrition rate” example above, consider rewriting the E-mail to see if this improvement significantly affects attrition rates.

For data-driven decision makers, this means looking at their historical data to see if there is any indication that the rewrite will perform well.

Along the way, you might find:

  • Social media posts shared in a lighter, more humorous tone gained more engagement;
  • Most of the people visiting the support center are existing customers, etc.

Now compare this to a non-data-driven decision example.

As the weeks passed, there was no difference in customer churn; Therefore, you can be sure that the problem is not an email problem, but something else.

4. Strategize

Targets for improvement were identified and the data analyzed to determine whether a new strategy should be adopted.

Next, you need to create an action plan to put the decision into practice.

The key at this stage is to clearly define what needs to be accomplished, what needs to be done, when, by whom, why, and what the desired outcome is, rather than setting vague goals like “Get it done before you get it done — by the end of the year”.

Measure success and repeat

The decision has been made and the outcome is complete, but that doesn’t mean your decision making process is over.

Look at the data originally collected and base your initial decision. Then, once the target deadline is met, compare the historical data to the new data collected and ask yourself: Did data-driven decisions have a positive growth impact on your business?

If successful, congratulations!

If it fails, it doesn’t matter. Sure, decisions may not have an immediate impact, but at least now you know what’s not working. Sometimes this is just as important as knowing what works.

As Thomas Edison said of the invention of the light bulb: “I didn’t fail. I found 10,000 ways that won’t work.”

Five, the conclusion

The Economist calls data “the world’s most valuable resource,” not oil, and with good reason.

The more data an organization has, the more they know about your buying habits and how you will respond to different messages.

He quoted a line from the Spider-Man comics: “Great power, great responsibility.”