Identify a customer’s likelihood to purchase products in the future. Craft the right campaigns to drive them toward this purchase decision.
Identify campaigns that might not work for certain customer cohorts. Create different messaging that is more likely to engage them.
Identify cohorts of customers more likely to respond to your campaigns, whom you wouldn’t have targeted otherwise.
Engage with customers who are likely to churn. Send them appealing discounts and offers to convince them of your product’s value proposition.
Never spam customers with campaigns they don’t need or resonate with. Make every interaction a meaningful one.
Identify customers most likely to perform certain actions and craft campaigns that resonate with their interest for better ROI.
Instead of bombarding all your customers with the same message, imagine if you could only send conversion campaigns to those most likely to convert. This would dramatically increase your conversion rates, and also reduce spend by cutting down on the cost of reaching uninterested customers.
Predictive analytics enables brands to understand how customers think and predict how they would behave. Using this data, brands can create more relevant marketing campaigns that reach customers when they want to be reached.
Marketing strategies of the past relied on generic message blasts sent out to the entire customer base. Today, however, customers are expecting greater standards from brands. It’s no longer okay to send irrelevant messages to customers or spam their inboxes.
Predictive marketing enables brands to move beyond campaign-centric messaging and be customer-centric instead. To be in sync with customers, brands must leverage predictive marketing technology to gain insights into customer behavior and get a peek into future trends.
In this whitepaper, we take a deep dive into how you can use predictive analytics to increase conversions, reduce uninstalls, and reactivate dormant customers.
Predictive analytics run on an AI-powered model that analyzes customer data over a period of time to identify trends and predict customer behavior. The predictive marketing software collects both, current and historical data and leverages machine learning to identify patterns and give futuristic insights.
This enables brands to create happier customer interactions and build brand loyalty while cutting costs of campaigns that don’t deliver great ROI.
How would you like it if you received an email about a cheesy burger just when you’re trying to start a diet? Predictive marketing aims to eradicate such scenarios and enable every marketer to send relevant campaigns to customers.
Using predictive analytics marketing, brands can break marketing data down into insights that matter: which customers are more likely to click on a campaign, for example, or which ones are least likely to convert.
Imagine if you’ve identified a cohort of customers who are most likely to uninstall your app, using predictive marketing tools. You can now send these customers a campaign that reminds them of the value of your products and entice them to stay on, preventing uninstalls.
At the same time, imagine that you’ve identified a segment of customers most likely to convert from a campaign. You can now reduce the discount you’re offering to this segment, and save costs while promoting customer engagement.
A prediction in marketing campaigns helps you predict actions a particular customer might take in the future. You can use this information to improve your marketing tactics and push the customer further down the sales funnel.
Predictive marketing strategies can help you increase brand loyalty and revenues from existing customers and create personalized experiences for potential customers and nudge them toward conversion.
Predictive advertising leverages predictive analytics marketing to identify trends from customers based on their past purchases, behavior data, and propensity models built from existing customer data. Advertising and marketing campaigns can also leverage these predictions to improve the experience for new customers.
A marketing strategy based on predictive analytics helps concentrate marketing efforts into channels that produce the best ROI. Instead of trying to reach every customer segment available with the same marketing campaign, predictive tools enable marketers to create tailored experiences for each cohort.
Predictive analytics also enables brands to accurately predict future purchases, so that brands can send out messaging across different marketing channels and ensure that the customer fulfils the purchase.
Instead of sending messages across multiple marketing channels, predictive analytics marketing helps you leverage customer insights and predictive technology to send messages at the right time, to the right people, across the right channels.
Predictive analytics marketing can be utilized to improve every stage of the customer lifecycle, and thereby, improve the overall customer experience with the brand. There are multiple successful examples of predictive analytics in marketing campaigns, deployed by world-famous brands such as Netflix, Spotify, and more.
Take, for example, a banking and fintech company that is trying to improve the customer’s lifecycle. This brand can utilize predictive marketing to gather current and historical data about a customer’s preferences and purchase behavior.
Using this data, the brand can suggest a particular feature or raise targeted awareness about a suitable credit card. Brands can try to customize all marketing campaigns based on data from predictive models. (The more data you feed to the machine learning algorithm on the predictive model, the better the results.) This insight can help create personalized experiences that make customers feel more connected to the brand.
Predictive analysis helps brands leverage behavioral, psychographic, and demographic data to create futuristic predictions on customer behavior. Marketers can analyze these insights to take data-driven decisions about marketing campaigns in the customer journey.
This can help marketers improve customer acquisition strategies by creating the perfect onboarding journey, and also increase retention by creating better experiences overall.
Marketers need to quickly understand what is predictive marketing, how different segments can be engaged with personalized experiences using predictive marketing automation, and analyze results to optimize future campaigns across all platforms and channels.
Imagine receiving an email about your favorite show’s newest episode, just as you begin searching for it. Or imagine receiving a notification on the website prompting you to click on the ‘Watch Now’ button, just when you’re searching for the button. These are some of the amazing things brands can achieve using predictive marketing.
Predictive data can help brands take their engagement game to the next level. Customers love when a platform tries to engage them by showing them what they want to see, even before they search for it. In fact, multiple predictive marketing case studies have shown that customers love personalized marketing and personalized recommendations. Any marketer who tries to create a personalized experience using predictions from past data is winning by engaging customer in the right manner.
The future of predictive analytics looks very promising. Machine learning is constantly improving itself, and every predictive model is going to be more accurate than the last one, which reduces the cost incurred to manually gather data, leaving more room in marketing budgets for other strategies.
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