By Saif Ahmad Khan
In the current global environment sales intelligence approaches are crucial for mainly organisations that seek to increase the level of sales performance and increase overall consumer satisfaction. Through analytics, firms can come up with a better understanding of their customers’ behavioral patterns, needs and wants and this will enable firms in coming up with the right sales strategies and customer experience. This move from hunches-based decision making to insights-based decision making is revolutionising the way businesses operate especially in the sales discipline to increased sales, better conversion rates and customer engagement.
Data plays an important role in the today’s sales environment in the following manner:
Information is the blood of contemporary approaches to sales. It is relevant in analysing the interactions that a customer has with a firm starting from the time when he/she first gets in touch with the firm to the time when he/she is following up on a previously purchased service or product. Most importantly is that real-time data is vital in helping the sales teams to get insights on the trends, forecast and improve on how to reach out to customers. For instance, using past purchase histories, firms can discover signs that a particular customer is about to reorder, or, in contrast, is considering a competitor’s product. Such information lets the sales teams approach the customers before they develop a problem then help them to solve the issue while still being their customer.
Using Tools of Sales Performance Analytics
It stands to reason that one of the most effective forms of big data for selling is predictive analytics. The data analysis enables predictive models to give insight on the future sales results, this can aid companies to direct resources to the probable profitable leads. For example, predictive analytics can help in scoring the leads to the likelihood of conversion, and as such, the salespersons sell to the companies most likely to make the purchase. Apart from that, it also helps to raise the general conversion rate since sales representatives can devote more time to the leads who are actively willing to make a purchase.
Also, predictive analytics allows the sales managers to see potential problems long before they must escalate to other stages. For instance, once a manager has reviewed sales performance figures, he or she is likely to realise that a specific sales staff member is under achieving. With this insight, the managers can find out early that the representative requires extra assistance or remedial training to correct his or her behaviour. This was because in reserving resources, potential problems are addressed before they cause major greatly effects on the company’s bottom line.
Personalising Customer Interactions
This is probably one of the biggest strengths of data-driven selling: it fosters personalisation of the customer engagement. The customers of today’s economy are no longer satisfied with a simple exchange with businesses; they desire to be recognised and appreciated. In this manner, the sales force can ensure that it designs and executes a customer experience that will suit each of the customers.
For instance, information regarding a customer’s behavior regarding a certain brand can be used to dictate how the sales representative communicates with the client. If a customer has indicated especially an interest in a specific type of products within the company, he or she can be reminded of newer products of the same type by the sales team. Finally, knowing the kind of communication style that a customer prefers such as emails, phone calls or social media will assist the salespeople.
The benefits of personalisation are therefore not only improvement of the customer experience but also increases in sales vales. That being stated, customers who have a feeling that they are valued by the brand will continuously patronise this particular brand and recommend it to other clients, thus improving on the sales of the brand over the long run.
How to Increase Customer Satisfaction with the Help of Data Analysis
Satisfaction of consumers is directly proportional to the suitability of the sales plan of the company. Through data analysis organisations can identify needs and wants of the customers hence causes sales efforts to meet customers’ needs. The clinical alignment is essential for achieving customer experience, which will result in customer satisfaction and advocacy.
For instance, it is possible to identify that customers complain about long time between action and reaction, or long time it takes to make a sale. Solving these problems enables the companies to enhance the happy path for the customers helping the customers to have a smooth time dealing with the companies. Further, some dynamics that otherwise remain unnoticed can be seen and used to serve customers even better, e. g., by providing some percent off a selected product/service or changing the offer in response to possible customer complaints.
Conclusion: The Future Sales Is Digital and Is Based on the Analysis of Big Data
While organisations will gradually carry on striving in this highly competitive environment, there are critical success factors that will also remain highly important. Sales insights enable firms to make sound decisions for improving the sales mechanisms and offer value appealing to consumers. Striving for concrete results of analytics, companies aren’t only going to increase their sales even more, but they will also be building successful and durable partnerships with the customers. Ultimately, it will be those organisations that are capable of absorbing and leveraging this commoditised power of data that will flourish.
The author is founder of LEDSAK. (Views expressed are the author’s own and not necessarily those of financialexpress.com)