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Stop customers from leaving and increase your new customers by targeting promotions to the individual customer segments, and staying ahead of brand sentiment.
More companies are becoming aware of the amazing insights that can be gleamed from data science applications, and there are plenty of examples of how sales and marketing departments are capitalizing on these opportunities with data. By combining the powers of data science with the art of human sales, it is possible to greatly improve the landscape of marketing and the way it benefits both brands and consumers.
In advertising, and in-depth understanding of the market allows sales team members to develop a more personalized approach with their pitches. Data is used to understand connections between companies and their customers, see what aspects of the marketing strategy are absorbing most of the budget, and better understand how potential buyers will react to various sales pitches. Being able to quickly discover matching brands, identify successful efforts to fund, and customize the sales approach allows advertisers to be more efficient and produce higher quality work.
Data science is shaping the way you shop with a shift from brick-and-mortal businesses to online ecommerce. As the popularity of online shopping increases, so does the amount of data available to marketing professionals. Data is constantly being collected as you browse various websites. Information about which items are viewed, what is added to a shopping cart, and which items make it through the checkout process is all analyzed to give sales and marketing teams actionable insights into their products and offerings. Predictive analysis improves customer experience by suggesting new products based on likes and past transaction history customized to that individual shopper. This keeps consumers engaged with the brand, encourages larger purchase quantities, and increases the potential of a repeat customer. This data also predicts market trends, so businesses can plan for future products to feature and make sure they have the correct inventory quantities in stock at that time.
Major hurtles faced by marketing teams are figuring out how to stop customers from leaving their website, increasing website visits from new customers, and encouraging previous customers to repeat engagement. Data collected from customers’ browsing history and behavior I used to create customized promotions to target individual customer segments and stay ahead of brand sentiment. Predictive analysis uses data fed into an algorithm to identify groups of the population that might be interested in your product and targets those potential customers with customized marketing efforts. Information gathered from the data makes it possible to personalize recommendations to customers based on their developed preferences, which often leads to more frequent visits to the website and certainly more sales in a manner that benefits everyone involved.