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Predictive analytics are used to improve your marketing efforts and ultimately help your business grow. It is a method of anticipating and predicting the most likely buying behavior of consumers. It is made up of a set of techniques based on data analysis, enabling companies to set tailored and personalized marketing strategies and actions.
In this article, we will detail how predictive analytics for marketing can help your business thrive.
Gathering behavioral and demographic data can help you segment your prospects and customers to create new campaigns that are more adapted and targeted; this will make them more effective to capture prospects, move them further down your sales funnel and engage existing customers. To that end, predictive analytics are used as follows:
Depending on your target audience (or each audience segment), and which channels they use, you will want to personalize your content creation and distribution strategies using predictive analytics. In turn, that will help you offer more personalized experiences to prospects, increasing your chances of moving them up the sales funnel and converting them into customers.
You can combine the data from previous campaigns with the demographic information you've gathered about your customers to build a model using predictive analytics for marketing that will help you forecast future customer behavior. This will help you evaluate customers according to their likelihood of making a purchase or performing a particular action. A perfect tool to avoid needless marketing spending and improve its effectiveness since you always want to hit customers in a way and at a time when they will be most receptive.
Building on the ever-stated goal of marketing of hitting customers when, where and how it matters, lead scoring can help you avoid the wrong moves, by qualifying and prioritizing prospects according to their interest, urgency and purchasing power.
With lead scoring, you assign values (points) to individuals based on where they are in their buyer's journey (or sales funnel). The higher the score you assign to a prospect, the more qualified they are. Scores are generated according to the data you have about those prospects; e.g., the information they formally submit to you, the actions they’ve taken, and how they’ve engaged with your brand across different channels…
You can even create grade your prospects differently according to the type of lead (or the segment, etc.). This will help you predict future buying habits and help your marketing team focus on where it matters most to lead more prospects down the sales funnel. Send the highest scoring prospects to your sales team, and avoid the lowest ones entirely; as for those in-between, nudge them accordingly with strategic marketing efforts.
In the same way predictive analytics for marketing can help you segment and target your audience, they are also used to create an essential metric: Customer Lifetime Value, also known as CLV. Using historical data, you can identify the most profitable customers, the marketing activities that generate the best ROI, and the segments of your audience that are the most loyal.
That metric is important on the long-term, as you can then estimate the future total value of your customers, and therefore how you should tailor your marketing budget and what ROI (or ROAS, for Return on Ad Spend) to expect.
Segmenting your audience also serves to create identification models based on customer data. Those predictive models will help you identify prospects who are similar to your current customers, so you can target them effectively and develop them into leads and customers.
Furthermore, combining customer behavior data, prospect information and historical purchase data will also help you understand what your current customers expect and want from you. That information will then prove key in predicting their future wants or needs. Armed with this knowledge, you will thus be able to develop new products or services suited to answer those wants and needs, adapting your offering even before your customers even express their want for change!
Predictably, you will want to use your marketing data to cross-sell or up-sell to your customers, to increase your profits. And by identifying patterns of behavior, you can target your existing customers more effectively.
For instance, if you see that a significant portion of your new customers end up buying another specific product or service, you might want to create a marketing campaign to specifically upsell them on this product or service, a strategy that required predicting behavior through combining sales and marketing data.
We have seen predictive analytics for marketing are used to produce churn analyses. But you then also need to act upon it, since if left unattended, it may prevent growth altogether. You thus always want your growth rate to be higher than your churn rate (calculated as the percentage of regular customers you lose within a specific time frame). For instance, if there is a specific pattern in the way you lose customers (if you leave them without specific marketing efforts for a certain period of time, if your offering doesn’t evolve fast enough over a certain time, etc.), you can then work to change that to prevent churn before it even happens.
The more information, the better. Predictive analytics for marketing can help you achieve more precise targeting and messaging to help you build stronger, more authentic campaigns that connect with prospects and customers. This will ultimately increase your results. Building on everything you have learned from points 1 to 9, you will therefore create better-designed campaigns by better predicting their results.
Predictive analytics for marketing can thus not only reduce risk by eliminating a great deal of guesswork from your process, but can also lead to faster growth and greater ROI for your business. Now, of course, incorporating these tactics doesn’t necessarily guarantee success, but it can increase your chances of success by informing your future practices and decisions.
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