Marketing

Why sales will need AI solutions in the future – eCommerce Magazin

Artificial intelligence is no longer a dream of the future. Autonomous vehicles in road traffic, intelligent robots in production or voice assistants on our smartphones show us every day how far the development of AI technologies has already progressed. But even where you would not expect it to be so in everyday life, AI is increasingly acting as one of the decisive drivers. For example, in the sales cycle of German companies.

Providers of revenue intelligence solutions support companies and, above all, sales employees in not only optimizing their sales structures with the help of intelligent technologies, but also in creating the optimal conditions for their employees in order to be optimally equipped for the new challenges in which they are constantly developing to the changing e-commerce and retail environment – and not only to achieve your sales goals, but to exceed them.

Sales cycle: Introduce efficient processes in sales

As a rule, a complete sales cycle includes dozens of applications and systems, all of which have the same goal: to satisfy employees and customers. Nevertheless, many of these solutions are still used independently in German companies. A lack of coordination and communication between applications and data sets can quickly become a bottleneck. Processes take longer, errors are recognized too late or not at all and the individual solutions do not learn from each other. This puts further pressure on employees who usually have high goals anyway.

Such partially inefficient processes can still work for a long time if a company is large and liquid enough and the losses generated as a result are not noticed. However, the competition in sales has changed so much in recent years that this buffer is no longer sufficient in the long term: digitization, ever new competitors due to lower market entry thresholds and the increased pressure on retailers and sales employees due to the pandemic have new conditions created.

Merge data from internal processes

At the speed that e-commerce and retail are now displaying, companies can no longer afford to run internal sales processes largely uncoordinated next to one another. Customers are demanding ever faster results and flexible offers, employees are demanding performance-based remuneration that is always precisely calculated. And all of this in a changed environment that will also change faster and more rapidly in the future due to the growing integration of sales software and IT solutions.

That is why it is important right now to join loose ends and merge data from internal processes with the help of intelligent software. This is the only way to analyze the cost structure of individual sales to such an extent that they can be classified as “good” or “bad”. In addition, high-performance sales cycles can be identified, so that employees can also gain insights into whether a further increase in success is possible by focusing on these sales.

Sales cycle: differentiating between good and bad sales

At first it sounds like a contradiction in terms, but not every turnover is one that benefits the company in the long term. If the effort involved in generating it is disproportionately high or if it may even run contrary to the goals of another unit and thus affect its sales, it makes sense to question the processes behind it.

Should sales in one area be restricted because the saved resources can be used to expand another area more effectively and profitably in the long term? Where can sales teams start in order to achieve the greatest possible benefit with the least possible effort? Which sales are associated with the best incentives to motivate employees as well as possible? Given the size and complexity of today’s sales cycles, it is virtually impossible to derive such knowledge from experience or gut instinct.

More transparency through intelligent revenue solutions

AI-supported applications such as Intelligent Revenue analyze existing systems on the basis of all available data. In this way, they enable a detailed insight into the cost structure of the various sales. This creates a comprehensive picture of how a company generates its sales and where resources are wasted or needed. With regard to the motivation of employees, it also helps to recognize to what extent the incentive remuneration promotes the correct sales behavior of the employees. In this way, companies can better coordinate their sales and remuneration structures in the long term.

But the analysis does not only work retrospectively. Based on the enormous amounts of data available in most companies today, the system can make sales predictable. A data-based look into the crystal ball that makes future decisions easier for those responsible for sales through fact-based recommendations. At the same time, the AI ​​compares predicted developments within the company with current and upcoming industry trends. In this way, these can be converted directly into possible recommendations for action.

LinkedIn uses Xactly’s intelligent revenue platform

One of the companies that has already optimized their sales cycle with the Xactly solution is the social media platform LinkedIn. LinkedIn has primarily used Xactly as support during its tremendous growth in recent years. “With Xactly, LinkedIn has grown from 125 to 5,000 employees,” reports Matt Sheppard, Global Sales Leader at LinkedIn. “It is a natural transformation to keep checking and adapting what works for what reasons. This also requires the right mindset to find out what we can achieve with $ 30 billion and more. Xactly helped us do just that. ”

Basically, at a time when the importance and quantity of data records in companies is continuously increasing to immeasurable quantities, experience and manual evaluations are no longer sufficient to achieve optimal analysis results. Without AI tools and intelligent platforms, companies will find it difficult in the future to expand their sales cycle optimally and, above all, competitively.

Also read: Digital strategy: Linking analog and digital sales channels with one another

Sales Cycle Xactly
Jamie Anderson is Xactly’s Chief Revenue Officer. (Image: Xactly)

About the author: Jamie Anderson is the chief revenue officer at Xactly. In this role, he leads Xactly’s goals of increasing sales and increasing profitability. Also, improve operational efficiencies for the world’s leading sales organizations. He is a tech leader, known for building and scaling sales and go-to-market organizations. Prior to joining Xactly, Jamie Anderson held senior positions at Adobe, Marketo and SAP.