Why AI-based sales software is cloud-based
Trend in B2B sales shows clearly towards expanding services from the cloud.
The Internet has long since ceased to be just a means of communication. Companies today obtain a wide variety of software and countless services directly from the cloud. B2B sales can also benefit from cloud-based AI software.
The development of cloud computing began around 60 years ago. To understand what was going on at that time on a technical level, you first need to detach yourself mentally from what we know today by a cloud – or cloud computing.
There was not yet a Google, whose various cloud services we now use on a wide variety of devices such as tablets, smartphones or PCs. There was also no Microsoft, which today provides individuals and companies with a wide range of cloud technologies and solutions.
In the 1960s, the first ideas emerged about how to make specific IT resources, such as computing power and applications, available to a broad mass of people.
For this purpose, there were host systems with central computers. An Internet as we know it today did not yet exist. The best-known example is probably DATEV.
The IT service provider for tax consultants, auditors and lawyers handled all services via a computer centre.
At some point in time, different computers of the same organisation are networking with servers via cable (Ethernet). PCs and servers shared the computing power, whereby you had to install Updates each time centrally.
Sales software for customer analysis from the cloud
Finally, in the 1990s, the opening of the World Wide Web to the public and the emerging triad of website, web browser and web server paved the way for the cloud. The so-called multi-tenant software architecture came up, which allows several companies to use the software simultaneously via a browser.
The pioneer was the US company Salesforce with software for CRM.
Since around 2010, the cloud or cloud computing has been the norm. The collective term “cloud computing” describes the provision of various hardware and software solutions via the Internet.
Users can rent computing power, storage space and software as required to expand or replace their infrastructure.
Nowadays, this is also possible for distribution software. However, this is no longer exclusively about software for managing customer data. It is also about software that analyses this customer data intending to determine the probability of particular customer behaviour. One speaks of predictive sales software.
That is an artificial intelligence (AI) based software.
Application areas of software for predictive sales
A sales software from the cloud, which determines the probability of individual customer behaviour, is used for the following sales scenarios, for example.
Opportunities for cross-selling and up-selling:
Such predictive analytics software uses data from existing customers to determine the probability of future purchases of complementary (cross-selling) and higher-value (up-selling) products or services.
Risk of customer churn:
Cloud-based sales software makes it possible to determine the probability or risk of specific customers migrating (churn risk). Accordingly, one speaks of churn prediction software.
Analysis of price strategies and pricing policy:
You can also use Predictive sales software to analyse the pricing strategy of companies and to identify possible contradictions in pricing policy. These can be very significant for the perception of the company and its products and services by customers. (software for pricing analytics).
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Sales software “as a service”
With cloud-based systems, the outsourcing of computer performance, storage space and software to the cloud takes place. In principle, it is therefore a question of outsourcing these capacities. The execution and use of sales software, for example, is then carried out entirely via the Internet.
Installations on local computers are no longer necessary.
Anyone who wants to obtain one of these three capacities via the cloud cannot avoid the three service models:
Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS).
Companies that offer SaaS keep specific software on their infrastructure, which is then used by customers on demand. The SaaS service model is therefore also known as “software on-demand”. The customer accesses the software via his web browser, which is also used in sales for predictive analytics, churn prediction or pricing analytics.
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Advantages of cloud-based sales software
When companies in B2B use sales software from the cloud, they benefit from the following advantages:
– Dynamic provisioning of capacities according to workload (scaling).
– Invoicing according to actual use or period of use (“pay per use”) and thus the elimination of a contractual commitment via licences.
– Low investment risk, as there is no need to purchase new software, for which you also need new hardware.
– No local installation of the software and therefore, no need to maintain storage space and other resources.
– Location-independent access from anywhere and any device possible.
The “Cloud Computing Survey 2018” of the International Data Group (IDG) measures cloud computing and SaaS trends among decision-makers in the high-tech sector. It shows the movement towards the expansion of services from the cloud. According to the survey, 73 per cent of the companies surveyed have at least one application in the cloud. About 89 per cent of the 550 IT-decision-makers named SaaS as their preferred cloud solution.
A survey by the “M&A consulting and tech investment company GP Bullhound” also proves the fact that SaaS solutions have now established themselves in almost all industries.
According to this, the SaaS market has reached a considerable overall size. The company calculated a market capitalisation of over 400 billion US dollars for the ten largest SaaS providers. On the customer side, solutions for business analytics are in particular demand.
