Predictive Analytics for Brands

Boost your marketing campaign using predictive modeling of consumer behavior. Find out more in this blog!

Powerful Ways to Boost Your Marketing with Predictive Analytics
Know your target market’s current and future needs. While tracking and addressing the current needs is rather easy, it is predicting the future that can seem bewildering. Fortunately, businesses can now leverage big data and predictive analytics to correctly identify the likelihood of future outcomes.


Your business can get the best assessment of what will happen in the future and use this knowledge to determine customer purchases, promote the right product or services to the right audience, cut down on wastage of resources and manage business expenditure more efficiently.

What is predictive analytics
Simply put, with the availability of big data and artificial intelligence it is now possible to calculate how likely a specific outcome is. Predictive analytics based on all available structured and unstructured customer data and historical actions can help your business immensely.

Why you need it urgently

Advances in technology, such as faster, cheaper computers and the availability of interactive, easy-to-use software, predictive analytics are no longer restricted to statisticians. There is an abundance of different types of data now available and more interest in using it to gain valuable insights. But in the growing volumes of data, individual insights very often get lost. It is possible though to break big data down by analyzing it with specific goals or categories in mind to get practical and actionable insights. Brands can use predictive analytics based on actionable data to perfect their key campaign metrics and create measurable campaigns.

What are the uses cases for brands?

Profile Customers and Visualize Customer Behavior

If your marketing database contains all information about your customer base across all your departments such as marketing, sales, customer support, and finance, then you can get deeper insights about your customers. Vendors, like Salesforce, offer a marketing cloud platform to help build audience profiles by combining data from multiple avenues, from CRM to offline data.   


Predictive modeling based around rules and data points you specify, like average order total, can help businesses identify and grow their most profitable customers. Identification models can then be used to acquire prospects with similar attributes. For example, a B2B technology firm can match the behavior of trail users to their customers who have paid for a subscription to identify trial users that are most likely to convert.

Large companies like Amazon and eBay have been successfully predicting customer behavior and preferences but the technology is now accessible to smaller companies as well. Propensity models like lifetime value, engagement likelihood, propensity to buy or churn, can be used to get “true” predictions about the next customer move. You can also leverage the data to personalize the customer experience and map out the customer journey. This helps eliminate any unnecessary steps when creating the perfect sales funnel, which improves your chance of boosting revenue.

Qualify and Prioritize Leads

Predictive-scoring can be tied into a brand’s existing lead data to qualify and prioritize prospects & leads based on their likelihood to take action. It is also possible to segment leads for personalized messaging through automated segmentation. This helps sales teams prepare and apply better strategies to move the sale forward and close. A comprehensive understanding of the prospect market helps sales teams create the right account based strategies to convert most of the leads into customers. Using data scoring it is also possible to predict the preferred price and product type that can lure a particular lead to convert. It allows marketers to create and optimize marketing campaigns that generate higher quality leads and also accelerate the sales cycle.

Target the Right Customers at Right Time with Right Content

Today empowered customers to have high expectations about product, price, delivery, and service. Merchants and service providers now have much less time to convert to orders. Predictive analytics allows businesses to take dynamic and relevant decisions by giving them the knowledge to present the right product or offer at the right time through the right channel, all based on what best motivates the consumer to act. Predictive analytics models such as affinity analysis, response modeling, and churn analysis, can be used to identify hidden patterns and help determine the right channels and content for customers in order to get a quick turnaround. Predictive analytics gives you a holistic understanding of how to keep customers engaged and also their future needs to possibly re-convert them on your product or service offerings through up-selling, cross-selling or next-selling campaigns (like Netflix or Amazon). Backing your marketing campaigns with predictive data will definitely give the best possible outcomes and maximum ROI.

Key challenges

Harvesting the right data to direct future strategies can definitely lead to higher conversions, drive business growth and make each dollar spend go farther. Predictive analytics can help SMBs acquire new customers and also remain relevant to their existing consumers. Predictive data can be a powerful asset for your business for improving interactions and business strategy across multiple channels.



Credits: Originally appeared in DirectiveGroup

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