Valcon's experts on using AI to drive sales effectiveness

Of all emerging technologies around, artificial intelligence (AI) is touted to be the largest disruptor to ways of working in the sales function. Martin Berg and Rasmus von Rüden, respectively a partner and principal at consultancy Valcon, share how artificial intelligence can improve commercial excellence and business growth.

They key benefit of applying artificial intelligence in sales is that it powers decision makers to make informed decisions based on insights rather than instinct and experience. Also, it increases the speed and reliability of decision-making – pulling all relevant sources of information together and finding new structures and patterns – and helps sales leaders uncover and tap into new business models. 

Demonstrating the potential, an analysis by McKinsey & Company of more than 3,000 companies from 14 different sectors found that early adopters of artificial intelligence typically achieve 5-15% higher profit margins than their competitors. 

Getting most of AI in sales

But, when entering the new arena of AI-driven sales, many executives struggle on where and what to prioritise when they begin to build the case for investing in AI-driven sales – i.e. what could potentially bring the biggest commercial value and sales uplift when applying AI-driven sales?

Secondly, many executives are also not sure how to establish the right mindset and change in behaviour when working with AI-driven sales – realising corporate benefits while helping every individual understand ‘what’s in it for me?’. Thirdly, time to value and/or time to market is a frequently discussed topic when investing in AI-driven sales – how long does it take to begin to see a financial effect, and when can the solution be ready?

In particular, the third point about time to value and/or time to market is something that can give cause for debate – especially when leaders want the next-level growth and competitive advantage to be realised instantly. The benchmark for executives when investing and initiating new digital/IT projects is often +12-month projects with a significant investment attached.

Furthermore, the actual ROI will at best kick in some time after establishing the new IT solution and of course only if the organisation smoothly adapts to the new ways of working.

AI-driven sales guidelines

At the outset, the implementation of AI in sales should not be treated similarly to the usual IT or digital project. Here are five guidelines for successful implementation:

The biggest bang for the buck
Be diligent in understanding where to start your AI-driven sales journey and how it integrates with your overall business strategy. For example, how can we potentially achieve quicker results or reach commercial targets in one business unit by using AI-driven sales that can ultimately translate into the overall objectives of your organisation?

Start small to go big
Start with a limited scope to prove the value and effect. This could be building a pilot for AI-driven sales in a particular business segment or country.

Don’t wait for perfect
Use a pilot and minimal viable product mindset (MVP) to get started. Apply an iterative and small circle evaluation approach to quickly evaluate and fully grasp the learnings on AI-driven sales for your organisation.

Know your people
Do not underestimate the efforts to create commitment across your organisation – AI is a new concept, and we human beings are by nature rather reluctant to change. The change leadership efforts far outweigh the data science part of the project.

Be excited, not naive
AI-driven sales can be a game changer in identifying great potential for new growth and sales uplift and unveiling new ways of strengthening the commercial modus operandi of your organisation. However, it is important to not only understand the limits of AI-driven sales but also the limits of your organisation. How much change can your organisation adapt to and still be able to realise AI-driven sales benefits as fast as possible?

How AI sales works

By applying these guidelines, executives and organisations have can realise sales efficiency and effectiveness at scale. It allows to apply entirely new and intelligent insight by turning directly to the data and revealing customer and market dynamics through a bottom-up segmentation and analysis. How it works in practice:

• You source for relevant and available data sources (internal and/or external)
• You start compiling and structure the data so it can easily get applied in the AI modelling process
• You develop the algorithms, correlating the different data sources to find new insights and start training it so the solution quickly becomes smarter about insights (i.e. feed the algorithm with data and business logic) that could set you apart from your competition and enable you to respond to specific market conditions
• You user-test the insights and AI interface early on in the process to secure the best possible organisational involvement and ownership and train the organisation in understanding the new intelligence
• After a few iterations on the AI algorithm and AI interface to secure actionable insights in a user-friendly way – you are ready to start planning your sales activities, explore and close new opportunities with AI-powered insights