For many companies, big data is a scary, unchartered territory. However, in today’s digital marketing world, big data can unlock new opportunities and more strategic growth.
It can do everything from improving customer service and experiences to saving companies’ time and money.
You may still be wondering what exactly is meant by “big data.” Put simply, it refers to large data sets, some structured and some unstructured, that are analyzed to reveal patterns. These patterns in turn can help inform decision making. When it comes to marketing, big data isn’t the answer alone. The data needs to be properly collected, analyzed, and evaluated in order for the insights to make an actual impact.
So how do you take this sizable chunk of data and distill it into elements that are translatable to marketing? Well, keep reading because here are three ways to harness big data for smarter marketing decisions.
Table of Contents
1. Segment More Accurately
Long gone are the days when geographic targeting was considered niche. Thanks to big data, audience segmentation can get pretty granular. Meta’s detailed targeting, for instance, allows companies to launch campaigns based on mobile devices and speed of network connectivity! Along with this, you can segment based on a user’s travel preferences and other behaviors such as end of month purchasing habits.
Predictive audiences are becoming standardized in audience segmentation since they allow companies to better predict those who are likely to become customers. These audiences are possible thanks to AI learning and first-party data. Having this data means a brand can build out a predictive audience for those likely to purchase within the week. This audience segment will be built based on their recent content consumption, read emails, and internet activity.
A huge advantage of predictive audiences is that they don’t rely on third-party cookies. Because they are built on a company’s proprietary first-party data, they are a privacy-safe solution. As cookies are phased out, brands that are ahead of the game with predictive audiences will likely see better growth than those still relying on third-party reliant segmentation models.
2. Forecast Smarter
Big data takes most of the guesswork out of your marketing strategy. Rather than hypothesize how a campaign will perform or what your customer values, you can look at the data for this information. With this knowledge, you can forecast smarter and make more sound marketing decisions. You’ll waste less time, energy, and money on tactics that don’t perform. Instead, you’ll invest your efforts into tactics that really move the needle.
When it comes to forecasting, there are a few different types to consider. The first is time series analysis, which takes historical data — such as sales numbers — to predict trends. By looking at the different patterns of your sales growth, you can better account for what the future holds. Similarly, statistical demand analysis takes into account when your best sales period was and what the demand for your product will be in the future. For product launches, you can utilize test marketing by bringing your new product to a small group to create projections.
Some benefits of marketing forecasting include optimizing market activity and reducing customer turnover. You’ll also have a better sense of your inventory, knowing when your products are in demand and when to ramp up production. By analyzing historical data and market research, you can feel confident in your marketing decisions. This will put you in a better position moving forward, allowing you to keep a firm ground in the competitive marketplace.
3. Connect Better
Customers crave connection. They want to feel connected with the brands they purchase from. They want to be valued and seen as unique, meaning they are looking for brands to go above and beyond the traditional company-customer framework. This is a big task for companies, but one that can be addressed with the help of big data.
Connection and personalization starts the moment an individual interacts with a brand. The first time an individual engages with your brand is an opportunity to learn about their likes and dislikes. For example, Netflix’s entire platform is based on a personalized model. The streaming service recommends shows and movies based on past behaviors. Someone who watches a reality dating show like “The Bachelor” will likely be pointed to similar shows like “Love Island.” Personalized recommendations can go beyond shows to suggest products or services.
This level of personalization elevates the customer’s experience with your brand. They will feel loyal to you if they feel appreciated and understood. Even small personalization strategies like adding a first name to an e-newsletter or following up on their recent purchase goes a long way. Just be sure that your personalization strategies don’t go too far. You don’t want any privacy compliant issues. There is a fine line between truly knowing your audience and making them feel like you’ve violated their privacy by collecting too much data.
Conclusion
Big data is taking over — in a good way! Marketers that lean into this information will have better insights into their core demographic, meaning they can make well-informed predictions. This will lead to highly effective marketing strategies and campaigns that are more likely to engage customers and drive conversions.
