B2B Digital Transformation in Sales: Facts & Trends
Facts and trends about the B2B digital transformation
If you are leading a Business-to-Business manufacturer or distributor, you know it already: sales is currently experiencing a massive transformation across the globe.
Advancement in artificial intelligence technologies of the last five years is providing manufacturing businesses and distributors with new exciting potential.
According to McKinsey, companies now have at their disposal a set of powerful technological tools that are, when properly implemented, able to guarantee future growth:
“Advanced analytics and machine learning have given sales executives access to historically unprecedented amounts of data and computing power, allowing them to predict with a high degree of precision the most valuable sales opportunities.”
Predictive analytics is becoming increasingly popular in B2B sales. It helps B2B sales teams to become more efficient, sell more and prioritise customers and leads. Machine learning makes it possible to discover insights and to gain a look into the future.
The new customer journey is made of data and analytics.
This technological shift is happening when B2B customers are also modifying their buying behaviour and adapting to B2C practices. They research on the internet before buying, look for alternatives in forums, and read blogs. The buying decision is already taken, when the B2B buyer contacts sales.
Therefore, one idea to increase sales is to provide customers with the information they need to make a decision. Besides, make sure reviews from previous buyers and testimonials shine a light onto the benefits of your products and services.
However, both content marketing and customer referrals might not be enough in complex sales situations, where more than a dozen stakeholders and decision-makers are involved. Experienced sales staff might provide support, yet this help is also limited, especially when it comes to developing business in new areas.
Simple, straightforward purchasing processes are a thing of the past. B2B sales today is confronted with a very complex customer journey. This applies to both the provision of services and the sale of products. The customer journey to purchase involves today several stages, and these are likely to be interchangeable. Sector and product play a role in defining the buying journey and channels involved.
B2B selling has always been a reasonably innovative arena, however. While the focus recently has been on the B2C market, trends in artificial intelligence and machine learning are beginning to transform B2B as well.
The B2B Race Has Already Started!
The B2B market is currently undergoing a technological revolution where the most successful, and fastest-growing companies are using a scientific approach to deliver customer satisfaction and sales conversions. In many businesses, there has been a comprehensive switch from traditional field sales and marketing, to teams focused only on sales analytics.
B2B sales models are moving away from pure transactional one, where customers conclude a transaction and never contact the vendor again. This process is now in the hands of e-commerce. Manufacturers and even distributors are increasingly offering subscription-based services and products. This new offering requires a deeper understanding of the ongoing needs of a customer.
Data now drive sales. Successful companies are mining through sales data to discover cross-selling, reduce customer attrition and dynamically adjust prices.
Data now drive sales.
For most companies, it means understanding the best way to engage individual customers rather than using a one size fits all solution. It inherently requires technology to streamline and speed up the decision-making process, something that would take much longer under normal circumstances. If successful, companies get can steal a march on their competitors by using predictive insights to guide and support the sales process.
Advanced Analytics and Machine Learning To Make Decisions Faster
Which are the best sales opportunities? What sort of resources should you invest in each account? What is the best way to organise your resources and improve sales productivity?
These are perennial questions for any B2B business. In the past, companies would mix local knowledge and salespeople’s experience.
Over the next decade or so, the top-performing businesses will be swapping this approach for advanced analytics and machine learning – technologies commonly encompassed under the artificial intelligence umbrella. AI can significantly improve the productivity of sales and marketing teams.
AI can significantly improve the productivity of sales and marketing teams.
Data collected about individual businesses, for example, can be merged with swathes of external data and combined with predictive analytics software to drive better conversion rates, almost at the touch of a button.
AI can also assist with making sure you have the right people in the right positions. AI and advanced analytics can already help match the sales staff to leads to improve the chances of converting a customer. It can pair factors such as educational background and personality traits with behaviours that are associated with effective sales like listening skills and persistence.
This kind of analysis can help determine the type of salespeople a business employs, and what sort of training they are given to develop their skills.
Predictive Insights Can Help Guide Sales Processes
Having a look into the future is today possible in B2B sales. Predictive sales software accesses internal sales data, and if necessary, enriches it with external data-points. Internal sales data includes ERP sales transactions and CRM activities, where customers are identifiable and data quality of a reasonable level. External data might consist of historical and current customer information as well as demographic, firmographic and behavioural data. However, caution is required here, as the use of external data can lead to challenges in customer identification and data privacy.
Predictive and analytic insights take processes like generating new leads, prioritising leads, developing account-based marketing strategies and segmenting audiences to a whole new, scientific level.
Of course, there is still a human factor involved. Companies aren’t handing everything over to artificial intelligence with weighty but unfathomable algorithms. There needs to be a process of collecting and inputting data that must come from a variety of sources within the business. Lastly, key account managers are responsible for reacting to the insights and alarms that AI software provides.
A recent study by Forrester found that all but a few B2B companies used a fraction of their internal data. Employing predictive sales analytics and having a process to gather information and store it appropriately will inevitably unleash extra power for B2B businesses.
The challenge is organising the policy and processes that deliver this on top of choosing the right software solution and ensuring the appropriate high-performing staff are in the post.
Digital Transformation For B2B Sales: Facts & Trends – Summary
High-level technology and predictive software are the future of B2B sales. This revolution is already underway, and it is currently benefiting those companies that have adopted the new technology. Over the next five years, you should expect more and more businesses to change the way they operate by utilising new sales analytics software.
It’s no surprise that companies spend millions of euros in carrying out market research before coming up with a new service or product. They are trying to gain a look into the future; exactly what predictive sales analytics does in a much more granular and reliable way.
Gartner defines customer journey analytics as to the process analysing how a customer uses different channels to interact with a company. Predictive analytics and data mining are crucial components of customer journey analytics.
The B2B Innovation race has already begun. The businesses ahead in this race will shape their markets in the years to come.
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