The combination of big data and predictive marketing lets companies drive growth more quickly and effectively.
Entrepreneur Elon Musk once said: “If you go back a few hundred years, what we take for granted today would seem like magic—being able to talk to people over long distances, to transmit images, flying, accessing vast amounts of data like an oracle.” Marketers don’t have to go back that long to realize that what data can do for them today was considered impossible just a few years ago.
Predictive marketing propels a revolution in how companies engage with their prospects and sell their products. The combination of big data and predictive analytics lets companies find the right prospects and engage them with the most relevant offer. Now, when companies can predict who is a likely buyer, marketers can be more precise and effective.
Here are 7 business challenges that you can quickly solve using predictive marketing:
1. Engage the right buyer
9 out of 10 companies now use content as a part of their marketing. While it’s relatively easy to measure content engagement using analytics tools such as Google Analytics, the question is whether this content engages the people who matter most, i.e., your potential buyers.
This is where predictive marketing can help you create better content that engages the right people. There are several approaches for better engagement: for one, predictive marketing can analyze the path to conversion to see how each content piece contributed to conversion. Another approach is to analyze those who engaged with the content (if they are identified leads) and see how many of them have the potential to become prospective buyers.
2. Find new prospects
This is where every marketer stumbles. There are never enough new leads to curb sales’ appetite. With predictive marketing however, you can find new prospects that fit your buyer persona.
Using predictive marketing, you can build a quantitative model that describes your most likely buyer. This model will weigh indicators such as size, technologies and job titles that are prominent among your potential buyers. Then, it will search your house list for prospects with similar characteristics and high likelihood to buy.
3. Grow new markets
When entering a new market, you can use all of the knowledge that you accumulated in one market in order to quickly increase sales in the new market. For example, you can use predictive marketing to analyze the “DNA” of your US customers, and then using a predictive model, find similar potential buyers in Germany. Predictive marketing finds the common characteristics among your current buyers to help you find people similar to them in your new market. If you want to learn more about growing new markets with predictive marketing, download this ebook.
4. Cross-sell and upsell
When launching a new product or feature or when you have a very large house list spread across different products and services, you can use predictive marketing to match prospects to the products that he or she are most likely to buy. The secret is finding your ideal buyer persona for each product. And then, by enriching each lead in your database with thousands of data points (sourced from the Web and other databases), to find those who most resemble this ideal persona. Predictive marketing can also help you identify products and services that users are most likely to buy. This ebook is a great source for learning about cross-selling and up-selling with predictive marketing.
5. Predictive lead scoring
Predictive lead scoring predicts a lead’s likelihood to buy by weighing demographic and behavioral attributes. Each lead in the database then receives a score from 0 to 100, based on how likely he or she is to becoming a customer. Marketers can use predictive lead scoring in order to decide which leads should be sent to sales reps.
Imagine Adobe, for example. Adobe has multiple products that cater to different audiences: analysts, designers, illustrators, web developers and more. Now, when a new lead arrives, which product should Adobe offer first?
This is where predictive segmentation can help. Predictive segmentation can take this lead, enrich it with additional data sourced from the Web and add it to one of Adobe’s segments. The result is more relevant marketing and sales efforts.
Another great use of predictive marketing is recommendations. You probably already know recommendation from Amazon, where you can find offers that are related to what you’ve looked for initially. Birst, for example, wanted to understand which campaigns would resonate with its audience. They discovered that when they targeted companies who used competitor products, they were able to increase open rate to 35% and click through rate to 10%.
Predictive marketing revolutionizes business by replacing guesswork by data science. All of these 7 business solutions were considered magic just a few years ago. However, now, with the power of big data and predictive marketing, CMOs can be more effective, efficient and increase revenues faster.
About Ariana Beil
Ariana runs Mintigo’s Customer Success organization. She brings more than 20 years of experience in customer-facing leadership roles within software and SaaS companies. Prior to joining Mintigo, Ariana held senior marketing positions for several Silicon Valley software companies including Extole, Dasient (acquired by Twitter), and Fortify Software (acquired by HP). Earlier in her career, Ariana worked in enterprise software sales for IBM, Rational Software, and Pure Software. Ariana earned a Bachelor of Business Administration from The European University in Switzerland.