How predictive analytics can help businesses create a successful marketing strategy

To make your products or services successful in the market, you need to know how to market them. 

Predicting market trends, however, is easier said than done. Trends and customer preferences vary with time—the market is never set in stone.

That said, marketers can tackle this dynamic market by using the power of predictive data analytics, which involves using past and real-time data to predict future outcomes, helping marketers gear up for the future. 

In this post, let’s take a look at how predictive analytics can help marketers create successful marketing campaigns.

It helps you identify the right audience 

Marketers need to know who their target audience is before they start marketing their products and services. To be more precise, they need to have a deep understanding of their market—and predictive analytics can help.

With advancements in data collection techniques, large amounts of data can be collected, such as past sales figures, consumer behaviour and demographic data. The collected data can help businesses build consumer profiles that include consumer preferences, needs, and even the circumstances across every purchase that occurs.

With a clear picture of who their ideal customer is, marketers can predict the likelihood of success across their marketing strategies. 

Predictive analytics helps us develop marketing strategies

Just knowing who your customers are isn’t enough—you also need to know the best way to approach them and get them to notice your product or service.

Qualitative data, like age, gender and even race, can help marketers predict which kinds of marketing techniques will prove successful for a particular demographic. 

Studies show that 56% of all Australians research products and services online. Predictive analytics use quantitative data to help marketers predict how their target customers will react to their marketing tactics and how likely they are to purchase their offerings.

Predictive analytics helps marketers avoid mistakes

Marketing is like walking on a minefield—one wrong step, and it’s all over.

Sometimes, marketers try to experiment with different sales tactics, only to end up with a marketing failure on their hands. A failed marketing campaign means losing money and respect, something no marketer can afford to go through. 

If famous marketing failures of the past, like the introduction of New Coke by the Coca-Cola company back in 1985, have taught us anything, it’s that marketers should always look for red flags before going ahead with their campaigns.

Fortunately, with predictive analysis, marketers can use qualitative and quantitative data from their past sales and marketing campaigns to predict which strategies, approaches, and tactics will be successful and which won’t.

Marketers can improve a company’s relationship with its customers

Maintaining a good relationship with your customers is advantageous for any marketer—you want your customers to keep coming back for more. With predictive analytics, it’s much easier to maintain these mutually beneficial relationships.

Regular interactions provide plenty of information about each individual like their buying habits, tastes, preferences, and spending patterns. Using this data, marketers can now predict each customer’s journey and determine what kinds of products and services they may be interested in, in the future.

Knowing what a customer expects from you, and giving them what they want, can drive up revenue, loyalty and engagement in the long run—a hard-earned win for marketers in today’s market.

You don’t need a crystal ball to predict sales—you just need data analytics 

Predicting the future isn’t a thing of fiction nowadays, especially with all the technology that allows us to see what’s unfolding and what we can expect in the near and distant future.

Predictive data analytics has come a long way and with its insights, you can give your customers what they want, even before they know they want it.

How predictive analytics will change marketing

In a previous blog post, we discussed why marketers should be excited about data analytics. However, one thing we did not explain was how data analytics can transform the marketing industry. In this blog, we will be doing just that – more specifically, we are going to explain how predictive analytics works, and how it helps the marketing industry achieve better results.

What is predictive analytics?

Data analytics is a broad term referring to powerful platforms that process terabytes of data to yield unique insights. However, predictive analytics refers to a more specific form of analytics where platforms use historical data to predict future marketing.

So, what does this mean for you, the marketer? It means you will understand your customer better than they understand themselves, allowing you to sell products to them before they realise they need it. Moreover, you can find the optimal time to sell and set the perfect price structure to entice your customers. Major retail chains have been using this technology for years. For example, Target used data to identify female shoppers who were pregnant when they entered their second trimester, allowing them to market baby products to them. They were even able to accurately tell that a teenage girl was pregnant before her father even knew about it!

Predictive analytics in marketing

Predictive analytics works in marketing through a process called regression analysis. With regression analysis, a data analyst will take two variables and perform a regression coefficient, to discover the chances of the customer purchasing the product based on that variable. For example, a data analyst can take income level and product demand to perform a regression coefficient. If there is a strong connection between the two variables, it indicates that income level is a massive factor in product demand.

However, seeing the major contributing factors to customer demand is just the tip of the iceberg. With predictive analytics, it’s possible to map past data and predict future shopping trends. Whether you are in B2B or B2C marketing, you can anticipate what customers will buy before a purchase is made. In other words, you can easily identify high-value customers before they have even purchased from you. How can predictive analytics perform so many functions? By using a combination of response modelling, affinity analytics, churn analysis and historical data.

By investing in predictive analytics, you can perform several functions more efficiently. One function is customer segmentation, which involves dividing customers into different niches for more precise marketing campaigns. You can also create more detailed customer personas, which are the lifeblood of marketing. With analytics, it’s possible to incorporate information about future purchases, thereby creating personas that are more detailed than ever before.

You can then develop more precise marketing campaigns that will connect more closely with customers. It’s also possible to eliminate inefficient processes and reduce churn. Reducing churn ensures that customers don’t drift away. You can gain better insight into customers in danger of leaving and develop marketing campaigns that prevent them from leaving. It also becomes possible to automate market processes to find shortcuts, cut costs and save time.

Predictive analytics models in marketing

Predictive analytics identifies new marketing opportunities through three different models.

Propensity models: Analytics platforms can use historical data to see the chances of a particular customer closing a sale. Not only that – you can also identify the chances of a customer taking different actions like subscribing, unsubscribing, paying for the top-tier service and more.

Collaborative filtering: Predictive analytics can anticipate the type of products and services a customer is most likely to buy based on their past purchasing history. Thus, providing a fantastic opportunity to upsell and cross-sell. You already see this technology in action because digital giants like Amazon and Netflix are using collaborative filtering to sell additional products and services.

Cluster models: With this model, you can divide the customer base into different niche segments based on any variable like age, income level, demographics, and average order total. There are several different cluster models including brand-based clustering, product-based clustering, and behavioural clustering.

Key takeaways

Predictive analytics is an excellent tool that will change marketing because of its ability to take historical data and use it to make future predictions. Whether it’s digital or conventional marketing, analytics can deliver better insights, allowing you to develop more precise customer personas, identify high-value customers and precise marketing techniques that will yield better ROI in marketing efforts.

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