In the context of improving the success potential of their business, companies notice massive benefits when they center on customer behavior. Using data analytics and big data about customer behavior allows them to get relevant insights. Statistically, companies that leverage this type of analysis typically get 25% gross margin growth and 85% sales growth.
A lot of companies have adopted this strategy to personalize their customer retention and acquisition campaigns with successful results. There are multiple reasons for that, and here we delve into them further.
One of the best models of customer-based analytics is prescriptive analytics. Firms can figure out and decide their future goals and success potential by focusing most on customer behavior-centric drivers.
In terms of acquisition as well as retention goals, solutions based on these analytics are useful for marketing optimization, marketing attribution, risk/market segmentation, as well as assessment lifetime value.
Incidentally, the analytics helps businesses in ultimately tailoring their product/service offerings and promotional messages in a way that they meet the expectations and demands of the target consumers.
First, data mining is necessary to ask questions that would help you create and study the hypotheses from the answers. For retention and acquisition, you must center your questions around marketing and sales matters mostly. Some common examples here are:
Companies benefit highly in their customer retention, acquisition, and loyalty development initiatives while focusing on customer behavior data. They utilize approaches like customer journey analytics to influence KPIs and resolve issues during a customer's journey systematically.
The following are points to focus on most about customer retention/growth and customer acquisition campaigns individually.
Statistically, 67% of consumers churn from a company or their website due to unsatisfactory experiences. Among them, around 91% of people stop associating with the brand altogether instead of addressing the issue.
So, companies that rely entirely on customer feedback lose them more since a lot of them are not openly vocal about their satisfaction rate. Instead, focusing on analyzing customer behavior is a better alternative to figure out potential problems before unhappy consumers leave.
With customer behavior analytics as well as data segmentation, you can detect what value consumers are finding with a service or product. Such approaches help pinpoint the main constraints of the target users and companies make modifications accordingly.
In the current customer journeys, multiple touchpoints are important to notice across various channels. The journey itself takes a long time to cover. Statistically, 67% of marketers state the importance of developing a linked customer journey that encompasses all touchpoints/channels to achieve success.
However, this is not always successful, and most campaign messages are not imaginative or unique. Companies also face issues like fragmental data sources, cost limits, and unclear consumer insights.
Customers currently desire personalization and that is what organizations are focusing on to acquire their target audience. Consumer behavior analysis helps brands understand the various requirements, values, goals, and motivations of their consumers across the complicated multi-channel customer journey.
With approaches like “customer journey orchestration” and analytics, businesses can gather necessary and actionable insights to understand their personalized demands. This is useful to monitor the performance rate of the campaigns with customers and quantify the success rate of the journey overall.
With analytics and data mining efforts on the customer behavior points, companies can learn more details about their target audience. Thereafter, they can use these insights to frame their marketing and sales campaigns, helping them retain old and acquire new consumers.
Consider using a similar strategy to improve your business operations and growth rate effectively.
Artificial Intelligence | Nov 30, 2018»
Artificial Intelligence | Nov 30, 2018»
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