There’s nothing worse than working for months on a Campaign and realizing that the results aren’t as expected.
Unfortunately, most of us have been there. It’s impossible to predict how well a campaign will do before running it.
However, there’s a strategy that gets pretty close. It is called predictive marketing
What is predictive marketing?
Predictive marketing involves leveraging data related to audience behaviour, historical consumer research, purchasing history, website analytics, and other areas to forecast outcomes of marketing tactics.
Predictive marketing is fueled by predictive analytics, which dates back to the 1930s. It enabled mathematicians and computers to calculate and analyze the possible successes, failures, and results of various scenarios such as health or weather conditions.
Examples of Predictive Marketing
1.Predictive Product Suggestions
Have you ever considered buying a product, researched it, and then saw the same product or a very similar one in a promotion that showed up on a social media feed, in your email inbox, streaming platform, or another website banner? You’re not alone
Ecommerce site algorithms regularly collect data about your product interests based on what you’ve viewed or purchased from them. Then, these algorithms use that data to predict which products you’re most likely to buy next. This data is then used in the ad a prospect sees.
2.Predictive Lead Scoring
Predictive marketing doesn’t just stop after you get a contact, customer or lead. Once you build up your list of contacts, you’ll want to continue marketing to them or potentially direct them to a sales rep.
To avoid giving too much time to unqualified leads, brands can use tools like HubSpot’s Predictive Leading Scoring feature to analyze contact data profiles and estimate which prospects are most likely to make a deal in the future.
3.Automated Social Media Suggestions
A handful of social media tools, including HubSpot Marketing Hub, use predictive analytics and audience data to estimate and suggest the best times to post your content on a given channel.
Aside from predictive ad targeting, social platforms like Facebook and Pinterest also use algorithms to make predictions related to multivariate or A/B testing. With these types of tests, a brand will often submit two or more variations of their ad. When the ad goes live the social media platforms will immediately analyze which variation is clicked on the most and predict which will have the best conversion outcome.
4. Customer Churn Prevention Tools
While marketers primarily focus on gaining new customers, some might focus on creating content and offerings that continue to engage, retain, and even upsell current customers.
But, sometimes, it can be hard to tell when customers need new, engaging content or when they’re likely to churn. That’s why some major companies have implemented predictive analytics as well as marketing strategies to identify and re-engage customers that are about to churn.
For example, by tracking email engagement data and which contacts are less likely to open or click on emails, you can create a list segment of contacts that are at risk of unsubscribing and send a re-engagement email.
5. Predictive SEO Tactics
As a marketer, a major part of your job might involve creating blog posts, web pages, or other online content aimed to attract and convert audiences.
Because search engines can provide major traffic wins and brand awareness to brands, you'll likely want to produce valuable content that shows up on page one.
But, once you've landed your high search result page position and gained solid organic traffic, you can use predictive data to prevent the future loss of your ranking and all the traffic that comes with it.
This process, called predictive SEO, is when content strategists use traffic and search ranking analytics to determine if a web page is at risk of losing its traffic momentum from search engines.
What to Know When Using Predictive Marketing
It’s not perfect
It can be pricey
It requires data
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