Decisions, decisions. As a small business owner, you make hundreds of them every day – some easy and others difficult. When it comes to planning decisions, predictive analysis can help you make informed, logical choices when they’re not readily apparent.

Here’s how:

Start With A Goal

Data is what drives sound predictive analysis. The trick, however, is to not get overwhelmed by it. Between inventory numbers, lists of customers in your email database and so much more you may not know where to start.

By choosing a goal first, however, you can pinpoint what you want predictive analysis to do for you. For instance, if you’re trying to decide if you should run an email campaign to encourage repeat buyers, start by looking at past campaign data.

See how many repeat buyers responded to earlier initiatives, and what kinds of offers elicited the highest and lowest responses. By taking small “bites” like these, you can get your arms around the information and look for trends or other indicators that can help you decide if the initiative is worth it.

Maximize Your Tools

The days when only big businesses could afford to invest in the technology to use predictive analysis methods are long gone. With the introduction of platforms like Google Analytics and other social information gathering tools, small business owners have access to valuable data like never before.

In an instant, you can learn whether your videos on Facebook are being shared, and you can use this information to plan future videos. Or, you can see who is clicking on your Mailchimp email links, and use this information to predict how many recipients will take engagement to the next level.

The beauty of data today is that it’s continuously evolving and supplying new ways to predict future events. Platforms like LinkedIn, Google+, Facebook and Twitter continue to improve along these lines. And all you have to do is keep up with the changes to make the most of it.

Test and Retest

If your email campaign is to encourage repeat buyers succeeds, note the variables that contributed to this outcome. The time of day the email was sent, the offer it included, the subject line – all of this factors into whether future campaigns like this will deliver.

If you test a campaign that fails, keep track of the variables that may have led to this. Use your predictive analytical tools to pinpoint what may have gone wrong, so you can adjust your campaigns going forward. If all of your emails containing a link to your website went un-clicked, try including a link to a landing page that’s more offer-centric.

Each time you conduct a campaign, you’re building a database you can continue to mine. The more you test, the better the analytics. Remember, data doesn’t judge, it simply presents itself to help you make better decisions moving forward.

Predictive analysis is making it easier for small businesses to succeed or fail fast and grow from the experience. Whether you run a coffee shop, a welding business or an office supply store, it’s a tool you can use with data-driven confidence.