Predictive marketing sounds like a technology used in a Star Wars movie or TV show.
Predictive marketing is a technique that takes advantage of data. It helps determine what marketing activities will have the highest chances of succeeding. Companies who use predictive marketing use this strategy to make better data-driven decisions. It’s like Moneyball a popular movie about how the Oakland A’s reinvented baseball by using an analytics approach.
Companies who use predictive marketing, leverage data about audience behavior, consumer research, purchasing history, website analytics, and marketing automation analytics. It helps them forecast outcomes of marketing activities. Predictive marketing is like predictive analytics that uses data, algorithms and machine learning. It provide the best assessment of what’ll happen in the future.
Predictive marketing is accessible to all marketers and its helping smaller organizations leapfrog larger organizations with innovation. Marketers want to deliver happiness to its audience but it’s usually a mass, one-size-fits-all approach. With predictive marketing, organizations can provide a more personalized experience for their customers.
Predictive marketing is important because buyers have a lot of options. Marketers use predictive data science across channels to tailor messages to interested audiences. Predictive marketing is an essential part of marketing automation . Marketing automation is software that automates marketing activities such as email, social media, websites, and phone calls. With predictive marketing, companies can deliver strategic messages at the right time in the right place.
How to successfully use predictive marketing analytics
Predictive marketing is becoming more popular. So, let’s dive into four examples that you can help you better understand the power of this approach.
1. Predictive product suggestions
Amazon.com is a master at predictive product suggestions. They are a data-driven company that is customer centric. They know their customers want to be offered items that apply to them when they are shopping.
Personalization through predictive marketing has become an important part of buying decisions. Amazon has billions of data points to use to quickly test out things to see what works and what doesn’t. Amazon provides product suggestions on their website and via email. In fact, email suggestions convert better than on-site recommendations.
According to McKinsey, 35% of Amazon.com’s revenue is generated by its recommendation engine. Amazon uses item-to-item collaborative filtering, to help it scale recommendations in real-time. This personalized, predictive shopping experience helps Amazon increase the value of an average order. It also increases the amount of money generated from each customer.
2. Predictive lead scoring
Lead scoring is assigning a number value to a potential future customer contact with points. This helps marketers better rank leads on their readiness to buy. It helps companies know how interested someone is based on their digital body language
Lead scoring happens within a marketing automation system like HubSpot, Marketo, Pardot, and many others. Traditional lead scoring is based on current behavior. Predictive lead scoring is an estimate of what prospects will most likely engage with company. For example, HubSpot has a predictive lead scoring feature in their system.
Marketers have a big database of customer and prospect contacts. This database shows different levels of interest in the company’s products and services. Predictive lead scoring can help filter out the ones that marketing should concentrate on more. This process can help brands save time and resources. Why? Because it helps them focus on people that are interested in buying their products or services. Or subscribing to email newsletters.
3. Automated social media suggestions
There are some social media tools such as Sprout Social, HubSpot, Buffer, Hootsuite, and Cortex that use predictive analytics and audience information to estimate the best times to post your content on a social media channel.
Some tools can go deeper and provide social media content predictions. For example, Cortex uses artificial intelligence with historical data to determine what colors of a social media image will be most appealing to followers.
Sprout Social provides content suggestions to help companies pick which social media posts that followers are most likely going to engage with. They also offer suggested replies on social media to common customer concerns and questions.
4. Predictive search engine optimization (SEO)
Marketers and search engines are becoming more sophisticated. Brands want to show up on page 1 of search engines. The running joke in the marketing industry is that the best place to hide a dead body is page 2 of Google. Why? Because research shows 90% of searchers do not go past page 1 of Google. Research also shows that 90.63% of content gets no traffic from Google.
Getting search traffic is hard and search engines provide almost 30% of global web traffic. Search engines are important to a brand’s marketing efforts. SEO experts are turning to predictive SEO tactics. It helps them determine if a page is at risk of losing traffic momentum from search engines.
For example, HubSpot uses an at-risk content tool that analyzes data from an online visibility management platform, SEMRush. The tools also uses Ahrefs, an SEO tool that crawls and processes up to 8 billion website pages a day. This tool helps HubSpot determine when they are losing in rankings on search engines.
Bringing predictive marketing analytics together
Predictive marketing helps marketers use a crystal ball into the future by taking advantage of large amounts of marketing data. Predictive marketing is helping innovative companies like HubSpot and many others drive more sales.
If you are a marketer who is looking for new methods to make your campaigns more targeted and effective. Consider using predictive marketing at your company. It can be a tool to justify a new marketing campaign, tactic, or strategy.
Predictive marketing is not perfect. It can be pricey and does require a lot of data. However, it may be the competitive advantage you are looking for. It may help you take your marketing efforts to the next level.