Introducing Predictive Segments - Target Customers with High Probability of Purchase

With shrinking marketing budgets, the pressure on marketers to implement effective, targeted campaigns that increase sales and drive growth is mounting. A recent study by Gartner showed that only 9.5% of an organisation’s budget is now being allocated for marketing in 2022. While this may be higher than in 2021 (6.4%), it is still significantly lower than pre-COVID levels.

In a competitive market, using targeted campaigns that utilise business intelligence tools to predict purchase probability along with the customer lifetime value is crucial. The practice of audience segmentation can be taken a little further to become predictive segmentation, which allows businesses to predict the behaviour of their old and new customers. This allows them to use the right messages through the proper channels at the right time to convert them into paying customers and loyal advocates.

Tying in closely with predictive segmentation is customer purchase probability and customer lifetime value. Customer purchase probability is a measure of the likelihood that a customer will make a purchase from a business. Businesses need to understand because it can help them identify customers most likely to purchase. As a result, they can then allocate their marketing resources more efficiently.

While customer lifetime value (CLV) is a measure of the total value that a customer will bring to a business over the course of their relationship with the company. It is an important metric for businesses because it helps them understand the potential value of each customer and make informed decisions about marketing and customer acquisition strategies.

At Growth Jockey, we specialise in developing a comprehensive marketing strategy to ensure your brand is visible to your target audience at the right time to increase the probability of purchase.

Predictive Segments

Predictive segments are groups of customers identified as likely to take a specific action in the future, such as making a purchase or responding to a marketing campaign. These segments are created using predictive analytics, which involves analysing customer data to identify trends and patterns that can be used to predict future behaviour.

One of the key benefits of using predictive segments in marketing is that it allows marketers to tailor their marketing efforts to specific groups of customers who are most likely to be receptive to their messages. By targeting their marketing efforts to these segments, marketers can increase their chances of success and get more value from their marketing investments.

For example, a marketer might use predictive analytics to identify a segment of customers who will likely make a purchase in the next month and target this segment with a personalized email campaign.

Predictive segments can also help marketers plan better marketing strategies by providing insights into customer behaviour and preferences. Marketers can better predict customer purchase behaviour by analysing customer data and using this information to inform their marketing efforts.

A marketer might discover that a particular segment of customers is more likely to purchase when they receive a personalised offer or that a particular product is more prevalent among a specific demographic.

At Growth Jockey, we understand the importance of using predictive analytics to deliver customised marketing strategies that identify customer purchase probability. This allows your business to reach its full growth potential.

The Process of Predictive Segmentation

Predictive segmentation is a powerful tool business can use to identify and target their most valuable customers. By analysing customer behaviour and characteristics data, businesses can create segments of customers most likely to purchase and target their marketing efforts towards these segments to increase customer purchase probability.

One way to perform predictive segmentation is by using machine learning algorithms. By feeding data about customer behaviour, demographics, and other characteristics into these algorithms, businesses can create predictive models that can identify patterns and trends in the data and use these insights to create targeted marketing campaigns.

Predictive segmentation can be an effective way for businesses to increase customer purchase probability, as it allows them to identify and target the most valuable customers and create marketing campaigns tailored to their specific needs and interests.

Here are a few ways that digital marketers can use predictive analytics in their marketing strategy:

Customer Segmentation

Businesses can use predictive analytics to segment customers into groups based on their likelihood to purchase or take a specific action. This can help marketers tailor their campaigns to specific segments and increase the chances of success.

Customer segmentation is a valuable marketing strategy that divides customers into groups based on shared characteristics, behaviours, and preferences.

One of the key benefits of customer segmentation is that it allows marketers to tailor their marketing efforts to specific segments rather than treating all customers the same. By analysing customer data, predictive analytics can help marketers identify critical factors influencing customer purchase behaviour and create segments based on these factors.

For example, a marketer might create segments based on customers’ past purchases, demographics, interests, or web browsing behaviour.

Once customers have been segmented, marketers can use predictive analytics to predict which segments are most likely to purchase in the future and tailor their marketing efforts accordingly. For example, a marketer might target customers in segments with a high likelihood of purchasing with personalised marketing messages or special offers.

Customer segmentation via predictive analytics can also help marketers identify critical trends and patterns in customer behaviour, which can inform future marketing strategies.

For example, a marketer might discover that a purchase for new customers in a specific segment is more likely when they receive a personalised email or that a particular product is more popular among a specific demographic.

Personalisation

Personalisation is a powerful marketing strategy involving delivering customised messages, offers, and experiences to customers based on their interests, preferences, and behaviour. Predictive analytics is a valuable tool that can help marketers personalise their marketing efforts more effectively, mainly when predicting buyer purchase behaviour.

One of the critical benefits of personalisation is that it allows marketers to deliver relevant and timely messages to individual customers, increasing the chances of success for their marketing campaigns.

For example, a marketer might use predictive analytics to identify customers interested in a specific product or service and deliver personalised recommendations or messages to these customers.

At Growth Jockey, our tailor-made solutions reach your audience segments with personalised communication from your business. Our strategies will help you overcome all the obstacles in your marketing journey.

Lead Scoring

Lead scoring is evaluating and ranking leads, aka potential customers, based on their likelihood to convert into customers. Predictive analytics is a powerful tool that can help marketers score leads more effectively, mainly when predicting user purchase behaviour.

One of the key benefits of lead scoring is that it allows marketers to prioritize their efforts and focus on the most valuable leads, increasing the chances of success for their marketing campaigns. By analysing customer data, predictive analytics can help marketers identify key factors influencing customer purchase behaviour and use this information to score leads.

For example, a marketer might use predictive analytics to identify leads interested in a specific product or service and score these leads higher based on their level of interest.

Churn Prevention

Churn prevention is identifying and addressing factors contributing to customer churn, i.e., the cancellation of a service or subscription. Predictive analytics is a valuable tool that can help marketers prevent churn in a more informed and effective way, mainly when predicting and preventing user churn behaviour.

One of the key benefits of churn prevention is that it allows marketers to take proactive steps to address potential churn before it occurs, improving customer retention and loyalty. For example, a marketer might use predictive analytics to identify customers at risk of churning soon and target them with personalised messages or special offers to encourage them to stay.

It can also help marketers understand customer preferences and needs more deeply, allowing them to create more targeted and effective retention campaigns. For instance, a marketer might discover that a certain segment of customers is more likely to churn when they experience certain issues or challenges and take steps to address these issues proactively.

Conclusion

Predictive segments are valuable as they can help marketers plan better marketing strategies by targeting their efforts to specific groups of customers who are most likely to be receptive to their messages.

By using predictive analytics to identify trends and patterns in customer behaviour, marketers can gain a deeper understanding of their customers and create more effective marketing campaigns. With our dynamic marketing approach, we at Growth Jockey provide innovative solutions to put your business ahead of the curve.

At Growth Jockey, we are committed to delivering tailored solutions that effectively address the critical challenges faced by our clients across various industries, ultimately enhancing the user experience. Regardless of your company's size, whether it's a small-scale enterprise or a large corporation, you can now leverage advanced technologies to optimize your user experience. Take a proactive step towards unlocking the next level of growth for your brand by reaching out to us today!