In an era where big data and technological innovation are unlocking what seems like a new capability every day, it’s increasingly difficult to discern between a long-lasting trend and a fleeting fad. More practically speaking, for marketers, it muddies the waters when determining where to make significant investments
Case in point: predictive analytics and marketing models. If you’re not already making some sort of investment in models, you’re likely considering it, while simultaneously asking one or more of the following questions:
- “What do marketing models truly do?”
- “Are predictive analytics actually reliable?”
- “What’s the ROI of investing substantial financial and internal resources to create proprietary models?”
- “How do I leverage predictive analytics and models to noticeably improve our business?”
At SmarterHQ, we’re adamant proponents of the role of predictive analytics, machine learning, and models in driving behavioral marketing. Our Chief Data Scientist, Dean Abbott, is a world-renowned predictive analytics expert who has applied his expertise to innovate in the areas of fraud detection, survey analysis, planned giving, predictive toxicology, and missile guidance for more than 20 years. While marketers are abuzz about models, they’re not actually new, and they’ve been leveraged by organizations across countless industries to redefine business practices.
As you debate if and how substantially to leverage the power of machine learning, here are six ways marketing models and predictive analytics can create context that improves your marketing strategy immediately.
- Reengage high value customers before they leave your brand. By leveraging behavioral data to understand users’ engagement with your site over time, you can identify and reengage customers who used to spend a lot of money with your brand, but who have recently stopped engaging.
- Acquire new customers by knowing which shoppers may need an offer to convert. Using a modeled understanding of engagement over time, you can recognize users who have recently engaged heavily, but have never purchased from you. This allows you to consider delivering a personalized offer geared at customer acquisition.
- Protect margin by knowing who doesn’t need an offer. Using predictive analytics, you can identify shoppers who have a higher-than-average likelihood of purchasing in the near future, and exclude them from offers to protect margin.
- Prevent lost sales due to people experiencing issues on your site. Models can automatically identify when someone’s behavior indicates he or she may be having an issue completing a purchase. For example, you could reengage someone having problems entering their payment info with a real-time communication that offers a customer service number they can use to complete their order.
- Better distinguish disinterested browsers from super-engagers. By using models to automatically detect and analyze how deeply each user is actually engaging with your site, you can separate people with low interest from those who are meaningfully engaging with your brand, then focus efforts on the latter.
- Create personas unique to your brand. Is there a certain “type” of customer you wish you could pinpoint? Models can provide a path to better visibility of key customer groups or personas, including seasonal shoppers, brand-loyal customers and people who habitually only buy a certain product.
Predictive analytics and models may seem like pie-in-the-sky buzzwords. In reality, they’re immediately applicable tools that can improve the efficiency and effectiveness of triggered campaigns, your website, promotions and more. If you’re ready to learn more about how models can be applied immediately to your brand, request a demo and let’s get cracking.