“Big data” has become quite the buzz word for modern marketers in the last few years. But what exactly does it mean, and how can you use it to your advantage to enhance your marketing strategy?
By definition, big data is large data sets that can be analyzed to reveal patterns, trends, and associations. In other words, it’s data that you can take action on. Thanks to intelligent technology, we now have access to all kinds of data. The trick is understanding how to use it correctly.
Step 1: Review current data
Take a look at data currently available to you for your customers and prospects, and ask yourself these questions:
- How much data do I have? Is your volume of data enough to draw conclusions from, or do you need a larger database to see results?
- What type of data sets do I have? Is it basic information such as contact details, or does it dig deeper into lifestyle habits or preferences?
- Do I trust the data? This is key. How clean is your data? If you don’t trust that it’s accurate, then you’re essentially starting with a blank slate.
Note: One of the biggest challenges in managing big data is lack of consistency and having clean, correct data. Make sure there are measures in place to minimize this risk so you can be the most effective with your marketing.
Step 2: Determine what you want to track
Don’t just collect data for the sake of having data. Data is worthless just sitting around in a database somewhere. Plus, high volumes of data can quickly become difficult to maintain. Rather, make that data work for you. Determine the campaign’s goals and if you have the data necessary to segment accordingly. If not, take steps to collect the missing data points. Alternatively, perhaps there are questions you need answered that don’t directly tie to a campaign. Can you find the answers to your questions in the data you currently have, or will you need to collect more?
Step 3: Collect the data you need
There are several ways to collect data, and which option or combination of options you choose will depend on what you want to track. Depending on the type of data needed, collection could be done by phone, in person, online, transactional, or observational. Figure out where you need to go to get the data. Some great sources include:
- Social media
- Customer managed profiles
- Google Analytics
Step 4: Segment your audience
Whether using data management software, a CRM or spreadsheets, find your desired audience for a campaign by filtering particular data sets and cross examining sources to find patterns and draw conclusions. Be open-minded about your findings. You may discover you need to tweak your marketing message based on your audience. Or, you may find new audience segmentations that can be worked into your overall marketing strategy.
Step 5: Execute targeted marketing campaigns and measure results
With data in hand, you can begin executing campaigns to your audience segments. Don’t feel you need to do everything just because you have the data available to you though. It’s often best to start small with low risk segments. Learn, adapt, and grow from those and work your way into larger, more complex campaigns.
Marketing channels that tend to work really well because of their high degree of personalization with variable data include direct mail, email, and retargeting.
As with any campaign, you must also track your results. This is especially true with segmented lists, since they are an ever-evolving piece of your marketing. Note if the campaign did well and who the audience was. If it didn’t perform as expected, was it due to the message, the timing, the audience, or another factor outside your control? Don’t forget to also track the data about your audience from the performance of the campaign itself! This provides even more data at your disposal for a future campaign.
The more you experiment with big data, the more insight you can gain to better target your audience, drive sales, and increase customer engagement. If you haven’t utilized your data to its fullest yet, start small. Test out segments, track your results and adapt your approach to maximize your return on big data.
Content from this article was inspired by a panel presentation at the 2016 Franchise Consumer Marketing Conference in Atlanta, GA. In addition to the tips presented here, it was recommended that franchisors make key data sets available to franchisees to help improve their performance. Examples of such metrics include new customer return rate, repeat customer return rate and average sale volume per transaction.