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Robotic Selling does not make salespeople redundant, but more successful

SalesTech, Integrated Sales Platforms, Predictive Analytics – Nevertheless: Sales People Remain at the Center.

The possibilities of digitization are changing sales and the role of sales staff. On the one hand, because today’s mature, digitally informed customers want to be addressed differently, and on the other hand, because sales support systems are able to analyze the interests and potential of possible customers long before personal contact with sales. However, modern integration platforms, automated processes and machine learning models that provide sales with predictive analyses of closing probabilities, for example, do not make sales staff redundant – certainly not in the B2B sector. They make them more successful. They help sales staff to concentrate fully on their central task: communicating with the customer.

Research online, purchase offline

Today, customers research autonomously on the internet, long before any personal contact with the company. The formula is often: Research online, purchase offline. That’s why, despite all the digitization, sales staff still play an important role in many industries, in the B2C sector as well as in the B2B context. Many bank and insurance customers, for example, still want personal service, and in the B2B sector, buyers value contact with a key account manager who knows exactly what they need and why. A purchasing department, for example, will not order capital goods without first receiving detailed, individual and personal consultation.

Supporting sales through data

The consequence of the diverse and complex hybrids of digital and personal contact in modern decision-making and purchasing processes is not only that the customer is better informed about the product, but potentially also that the company is better informed about the customer. Companies must seize this opportunity and evaluate all the digital customer touchpoints that exist today in an automated way. With such a data basis, it is possible to optimally provide sales staff with information – whether it is about new leads or existing customers with cross-selling and upselling potential. Particularly in the B2B sector and with products that require intensive consulting, there is no way around digital support for sales staff.

The integration platform resolves data silos

Only when a company has complete access to all available data from relevant sources does the basis for effective digitization and automation in sales emerge. This requires an end of the silo landscape and an integrated sales platform. It is essential to synchronize the relevant data between the many systems in the company, preferably bidirectionally and in real time. At first glance, this may seem difficult in established companies – if only because they still operate many of their systems themselves: on-premises and not in the cloud. However, a wide variety of existing systems can be integrated with the help of suitable API middleware, regardless of whether they are marketing automation, ERP or CRM systems. Modern iPaaS technology (Integration-Platform-as-a-Service) is particularly attractive as a basis for the company-specific integration and automation platform. With such a cloud-based integrated enterprise data platform, companies can also connect any new external services from the cloud to their existing system landscape. In the process, on-premises hosted systems can also be hybrid integrated with cloud-based systems. An API middleware, such as the Marini HubEngine, which allows bidirectional synchronization of data in real time, is a central technological component for such a flexible system infrastructure. Sometimes, solutions such as the Marini DataEngine are also used for such an integrated platform. It handles the more complex integration and transformation tasks between systems, databases and services. This is because data often first has to be prepared, modified and enriched when integrating the sales systems.

The sales platform for ideal, automated sales processes

The iPaaS approach helps companies to create an individual integration and automation platform with conceivably little effort. The highly flexible sales platform ensures that marketing and sales managers can overcome all limitations when designing their ideal processes and fully exploit the advantages of a platform approach. There are almost no limits to creativity. If you want, you can literally draw your strategy-compliant ideal process on a white sheet of paper. The easily configurable automation platform makes it possible to rethink sales processes from the ground up, across all phases of marketing and sales operations: from lead generation to nurturing to sales. In the end, it doesn’t matter which specific systems are to be integrated and which new external services are to be integrated. That’s because the iPaaS approach overcomes system limitations. Even if a company designs a completely new automated process on its integrated sales platform, the salesperson can simply continue to work in the familiar environment, whether his CRM system is called Sales Cloud, Dynamics 365 or SAP C4C.

Integration across language and location boundaries

An integrated platform allows existing systems to be connected across different national and international locations of a company. Companies can then, for example, transfer best practices more quickly to other national sales teams. Powerful translation tools can then also be easily integrated into new automated processes, allowing employees to communicate much better and faster across national boundaries. Integrating data and systems makes sales teams more agile – and the company more successful.

Data Science supports sales

Once the relevant data, functions and systems have been integrated via the Enterprise Data Platform, it becomes possible to intelligently automate and control even more complex processes. Predictive analytics is used to train models which can then be used, for example, to determine automatically and in real time which new or existing customers are most likely to buy a particular product. These data analytics capabilities are combined and used to intelligently control automated processes on the integrated platform. In addition to all the data that is already available in the company – such as which information offers a lead viewed or downloaded and which mailings they responded to and how – external data can also be important here. For example, microgeography data offered by market researchers such as UNISERV or Dun and Bradstreet is often relevant. This includes information on the residential environment, such as social, age and business structure or purchasing power. All of this flows into the data analyses, on the basis of which models perform continuous scoring for lead qualification, for example.

Sales processes on a scientific basis

Beim Aufbau automatisierter Vertriebsprozesse erreicht man häufig einen Punkt, an dem im Prozess Entscheidungen getroffen werden müssen. Im Anschluss an die Gewinnung eines Neukunden will ein Unternehmen vielleicht nach zwei Monaten automatisch einen Cross-Selling-Prozess anstoßen. In solch einem Fall wird die quantitative Datenanalyse helfen, ein Entscheidungsmodell zu schaffen. Die komplexen mathematischen Formeln, die das Ergebnis der quantitativen Analyse sind, beantworten die Frage, mit welchem anderen Produkt der Neukunde in diesem Cross-Selling-Prozess angesprochen werden sollte. Wenn man sämtliche Daten, die zu den Kunden und ihrem Verhalten vorliegen, wissenschaftlich analysiert, kann Predictive Analytics zu jedem Neukunden automatisch ermitteln, welche Produkte bei ihm die höchste Abschlusswahrscheinlichkeit haben. So sieht ein Vertriebsmitarbeiter beispielsweise im Sales-System zu jedem Lead oder Kunden aus seiner Region die Kaufwahrscheinlichkeit für jedes der zehn Produkte aus dem Portfolio des Unternehmens. Dadurch kann er den nächsten Call immer mit dem Kunden führen, bei dem die Abschlusswahrscheinlichkeit für ein spezifisches Produkt am höchsten ist.

iPaaS and Machine Learning for intelligent sales support

It is also conceivable that the system will only show the sales employee those opportunities whose score exceeds a previously defined threshold. Today, machine learning models can perform a wide range of predictive analytics tasks, including churn prediction, lead qualification, segmentation, and potential analysis. A model can also decisively support sales as a recommendation engine. The use of integration and automation platforms does not want to make sales staff redundant. Through consistent digital support, salespeople should be able to proceed much more effectively and with greater focus than before. This increases revenue because salespeople can always focus on the most promising leads and existing customers thanks to the information from their automated systems. Sales reps no longer have to stare at a list of a thousand contacts and rack their brains over who to contact next. Models control and support the sales process on the company-specific automation platform – but they cannot visit the customers. Being able to really respond to the needs of today’s informed and demanding customers is a key success factor. Customers are once again moving to the center of sales work.

Conclusion: Sales success increases

Dozens of real-world examples already show the positive effects of modern automation platforms – thanks to ideal processes in lead marketing and sales that remove the technological barriers of existing system landscapes. The opportunities opened up by intelligent automation using integrated platforms and predictive analytics are immense. End-to-end sales support makes sales staff more successful and leverages previously untapped revenue potential. However, human contact remains essential, especially in the B2B sector. Perhaps it will even become more important than ever in our digitized future.

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