Predictive Marketing for Business

Nothing is more disheartening than finding, after months of effort, that your marketing plan isn’t producing the outcomes you had hoped for.

Too many of us may relate to this unfortunate situation. Although the campaign strategies were brilliant, the actual results fell far short of our expectations and the amount of participation was minuscule. After already seeing the demise of our project, we were then faced with the uncomfortable situation of providing our colleagues with inaccurate performance figures.

There is no way to know the exact results of a campaign before it is launched, no matter how much planning and preparation you do. But there is a tactic that comes awfully close to this problem.

It is predictive marketing!

Although the concept and future of predictive marketing may sound like something out of a science fiction movie like Westworld, the use of data to forecast an outcome is nothing new.

Predictive analytics, which has been around since the 1930s, is the engine that drives predictive marketing. Mathematicians and computers could now examine the likelihood of various outcomes, such as changes in health or weather, and make predictions accordingly.

Since the advent of “Big Data” in the early 2000s, a growing number of companies and advertising networks have used machine learning and other forms of predictive analytics in their marketing strategies.

Predictive advertising is now pervasive. I’ll give you a few examples and explain how companies can use them to their advantage below.


Using Predictive Analytics in the Real World

Automated, Predictive Product Recommendations

Have you ever pondered purchasing a product, done some research on it, and then seen the same thing, or one very similar to it, advertised in a promotion on your social media feed, email inbox, streaming service, or website banner? To put it simply, you have company.

Every time you browse or buy something from an online store, the site’s algorithms compile information on your preferences in products. Based on this information, the algorithms can foretell which items you will likely purchase next. This information is then incorporated into the online advertisement or promotion a potential customer encounters.

Forecasting the Value of Potential Leads

Obtaining a contact, client, or lead is merely the beginning of the predictive marketing process.

You’ll want to keep in touch with the people on your contact list or send them to a salesperson once you’ve built that list up, but you might waste a lot of time if they aren’t truly interested in what you have to offer.

Predictive lead score data like that described above can help narrow down a large database of contacts to the most promising leads when there is a wide range of engagement in your product, branding, or service. This could provide you an advantage over competing brands that lose precious time and energy on transactions that never materialize.

Automated Suggestions for Social Media

There are a few social media management platforms that use analytics and audience information to forecast when it would be most beneficial to share content. Some systems go beyond simply suggesting when to post material by providing in-depth predictions for social media posts.

Social networks like Facebook, Twitter, and Pinterest feature some predictive tools within their advertising platforms, on top of social media tools that can recommend strategies based on projected outcomes.

Methods to Reduce Customer Attrition

While the primary goal of many marketers is to acquire new consumers, others may instead work to maintain and grow their existing clientele through content and products that interest and delight them.

However, knowing when clients need fresh, interesting material versus when they are likely to churn can be challenging. That’s why some of the biggest corporations are using predictive analytics and other marketing methods to spot clients who are about to leave and bring them back.

Strategies for Predictive Search Engine Optimization

Blog entries, web pages, and other forms of online content geared toward attracting and converting audiences could make up a significant portion of a marketer’s time spent online. Producing content that ranks highly in search engines is important since it may bring in a lot of targeted traffic and increase awareness of your company.

However, after you have achieved a high position in search engine results pages and have garnered substantial organic traffic, you can utilize predictive data to safeguard against the potential loss of your ranking and the subsequent loss of traffic.

When content strategists employ data on traffic and search rankings, a process known as predictive SEO allows them to evaluate whether or not a website page is in danger of losing its momentum in terms of traffic from search engines.

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