Damien Acheson is the Head of Marketing at Cien, an AI-first company that helps sales leaders manage the performance of their teams and drive quota attainment.
A graduate of the MIT Sloan School of Management and Sciences Po Paris, Damien can often be found whistling on his way to work, or shuttling between Spain, France, the UK and the US.
In an exclusive interview with MarTech Vibe, Damien talks about the many facets of applying AI to sales and marketing – from sales force management to sales analytics, and from Big Data to machine learning and NLP. Excerpts from the email interaction:
What is the main problem that AI is solving for sales and marketing professionals?
AI is a new solution to one of the biggest problems faced by sales and marketing professionals: soaring customer acquisition costs. As new players enter your industry, your market saturates, making it increasingly expensive to acquire additional customers.
For example, if you operate in B2B tech, it costs 65 per cent more to acquire the same customer today as it did four years ago. These costs mean that spending more on sales and marketing does not generate a commensurate return on revenues, thereby affecting your company’s profitability. This was not the case 10 years ago when the industry was chasing “magic” growth numbers.
How can AI-driven sales analytics help generate better results?
To stay on top, sales and marketing leaders leverage AI and sales analytics to get a clearer understanding of sales and marketing’s contribution to the revenue generation process. Once you know how much value is being generated by each function, you’re able to identify what aspects of your acquisition funnel needs fixing, improving or expanding.
For instance, we offer a complimentary Hidden Revenue Assessment, which connects the dots in your CRM data to identify the skills and attributes that have the greatest impact on performance. Our AI engine has, of to date, already uncovered over USD 100 million in unrealised revenue due to gaps in selling behaviours and skills.
Speaking of data, Big Data analytics also helps prospecting teams; can AI speed up that process?
Certainly! AI-first apps can measure intangible factors such as a sales person’s work ethic, product knowledge or engagement ability. This helps your prospecting team to focus on developing the skills and enforcing the types of behaviours that are the most conducive to success.
Sales and marketing rely a lot on the quality of data. How can these teams ensure that the data collected is quality over quantity?
The great thing about AI is that it is excellent at detecting patterns. So even if your marketing or CRM data is inaccurate, you can still compensate for that using machine learning and natural language processing to see what’s going on in your business and detect trends before they impact your revenues.
Also, AI can help you understand the source of poor data quality, whether it’s due to a marketing tool, a sales process or an individual sales rep so that you can address the problem and ensure you have the best data going forward.
What’s the biggest challenge that companies face when it comes to integrating AI into their marketing or sales stack?
Many sales and marketing teams think their CRM data can be augmented by developing an in-house AI solution – this view, however, has been proven to be much more costly and time-consuming than outsourcing the work to proven AI for Sales solutions.
Other teams consider AI to be too invasive, complicated, or prohibitive in terms of costs; however, these perceptions are likely to change. The field might be relatively new, but it’s changing very rapidly. New open-source solutions such as TimescaleDB, for example, are driving the cost of AI down.
Will sales and marketing turn AI-centric anytime soon? What tools/solutions do you see turning AI-driven in the near future?
Absolutely! Machine learning and natural language processing (NLP) are already changing many business processes. Sales and marketing will become more personalised for the consumer, and more predictable for the vendor.
Since the system of record for all of this data is the CRM, I’d expect any CRM system to be the most impacted by AI. In fact, according to IDC Research, AI-powered CRM activities will boost business revenue by USD 1.1 trillion by 2021 and more than 50 per cent of B2B tech companies are already implementing or planning on introducing AI in their sales and marketing operations.
Social media is helping customers come closer to their brands. Yet, many are stuck in the decision-making step of their journey. How can sales reps leverage social media to help drive decision-making?
While, at first, a combination of direct messaging and chatbots on social media channels will probably become more attractive for sales and marketing, I think consumers crave for authenticity and reward brands that engage with them in a genuine and human way.
How important is it for companies to invest in state-of-the-art sales technology when they are building their MarTech stack? What sales tools are must-haves when it comes to better ROI?
Such investments are really important. But it is equally important to remember that technology is just a means to an end. In the extreme case, culture eats strategy for breakfast, and strategy gobbles up technology for lunch. This having been said, and all things being equal, I am seeing the proliferation of “customer intent” solutions and sales engagement platforms. I also see a huge uptick in the demand for AI-powered sales performance tools.
What are the top three MarTech trends one must look out for in 2019-2020?
More horizontal analytics across multiple data sets, greater levels of personalisation in the offline world, and increased integration of channels – primarily driven by AI and focused on the user experience above all.