Predictive analysis uses advanced analytics techniques that use previous data to foretell outcomes and predict prospects for the future. Using predictive analytics, identifying buying patterns will be much easier, which helps formulate business strategies and incorporate them into marketing tactics. It is something that helps combine the best of analytics and the best of marketing. 

Predictive analytics equips a combination of statistical techniques and data analytics like cluster modeling, predictive modeling, artificial intelligence, data modeling, data mining, and more. It is widely used in banking, stock market and finance, consumer behavior research, medical field and healthcare, sports management, and several others. The entry of predictive analytics in the marketing field is fairly new but expanding. Over the past years, predictive analytics in the marketing sector has increased by 23.2%.

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How to get started with predictive analytics in marketing?

Predictive analytics is a powerful plan of action that can render little to no use if the user is not aware of harnessing its potential. Being definitive and precise about what a marketer expects from predictive analytics brings clarity in using it. After all, data-driven marketing is the best way to get optimal and targeted outcomes. 

• Ask the correct questions 

Before diving into using predictive analytics in marketing, make sure to frame the correct questions that can help improve your reach. Define a purpose and goal about what final product you are expecting to unlock, what kind of data you need to achieve, what you plan to do with that data, how you are regrouping the available data to work in your best interests etc. 

• Collect the appropriate data from authentic sources 

There is an ocean of data that can get overwhelming and difficult to process. Being smart about what kind of data you would need and filtering out irrelevant ones to the current task is a crucial step. 

• Invest in reliable resources 

The most common reason that predictive analytics is not efficiently equipped in marketing yet is that it requires both engineers/technicians who can handle the data and marketing specialists who know how to implement that data in future projects. It is always better to coordinate with a team of professionals to get maximum results from predictive analytics in marketing.  

• Evolve with your strategy

Once a model is implemented, there is no guarantee that it is flawless in its predictions. Instead of feeling demotivated, keep working on the model, rectifying its flaws and technicalities. With every attempt, the insights and predictions of the model are bound to get more refined and accurate. Utilize the predictions in favor of a marketing strategy.

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Top brands that have mastered the use of predictive analytics in marketing

• Spotify – The company used data from their users’ playlists to invite other users with likely interests. The diversity of the users’ preferences was easier to decode by using other users’ preferences. They equipped the data in humorous anonymous advertisements under the “wrapped campaign,” which came up as a huge hit among the public. Improving customer experience is key to customer retention. 57% of customers have been notified that they would switch to competitor companies if there was better customer interaction. For example, Some of Spotify’s ads read, “dear …….., xxxx played ‘sorry’ 42 times on valentine’s day, what did you do?”
• Walmart – The shop analyzed customers’ buying patterns over long periods to arrive at predictions of their purchases the next time they visit. They analyzed more than 100 billion keyword searches every day and posed clickable call-to-action recommendations, relevant discounts, and more. It increased their overall sales by 15%.
• Netflix – This popular streaming platform uses large amounts of data from user searches, preferences in terms of duration, genres, language, etc., to arrive at personalized suggestions. Netflix has one of the best predictive analytics strategies for its marketing. 80% of Netflix users’ activities are guided by their recommendations.
•  Siri, OK Google, Alexa – Under the same category of virtual assistants, these AI tools use advanced predictive analytics to cater to their users. Their suggestions and recommendations are widely customized based on the user’s previous activities and searches.
•  Airbnb – The novelty start-up company has nailed its marketing strategies with more than 43000% success rate since its inauguration. They rely on the strategy to humanize data as much as possible to give the best user experience. They follow a game plan of implementing their models with data collected from searches and bookings over a specific period and conduct experiments to check its efficiency and to check places where it needs improvement.  

The applications of predictive analytics are endless, and its uses in the marketing sector remain untapped. Top global brands are figuring out ways to incorporate predictive analytics in their marketing strategies and succeeding with high ratings in their outcomes. Amazon and Netflix are two of the top brands whose predictive analytics are admired for the degree of customizations they provide for their users. The level of user satisfaction achieved through the platform’s personalization is a direct product of their advanced predictive analytics. This is a great start to propelling your brand and company on the digital forum.

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