Artificial intelligence (AI) is becoming mainstream in data-driven marketing and rapidly gaining traction in customer service. In this article we look at the usage of artificial intelligence in sales, another customer-facing domain where AI is rising fast.
Artificial intelligence comes in many forms, shapes, subfields and applications. From games, search engines and all sorts of targeting/personalization (news, ads and so forth) to intelligent document recognition, knowledge bases or image and speech recognition: we all use artificial intelligence, often without knowing it.
In recent years the number of applications and the fields where AI, machine learning and so forth are used has continued to grow with ample artificial intelligence business cases. From self-driving cars and the (serious) IoT (Internet of Things) to customer service (contact centers and chatbots), healthcare delivery, predictive analytics in pretty much all areas, security, facility management, the future of ERP: AI is a key element in it all and often cited as one of the key (group of) technologies in digital transformation and in Industry 4.0. The market for AI is growing fast as are the advances in use cases and the number of use cases. Especially healthcare is among the vertical industries where AI is showing its clear trasformational benefits.
Table of Contents
- 1 Artificial intelligence in customer-facing functions: focus on sales
- 2 Artificial intelligence and salespeople: the difference between selling and taking orders
- 3 Artificial intelligence and salespeople: the difference between replacement and augmentation
- 4 Einstein and geniuses: artificial intelligence in the sales cloud and beyond
- 5 Key benefits and impacts of artificial intelligence in sales and sales management
- 6 The usage of artificial intelligence and the need to be more human in sales (management)
- 7 What can artificial intelligence help us achieve in sales?
- 8 AI in sales: does it pay off?
- 9 Artificial intelligence in sales in practice: some examples and solutions
Artificial intelligence in customer-facing functions: focus on sales
If we look at cross-vertical functional applications it probably won’t come as a surprise that, on top of information management, marketing sticks out in this data-driven marketing age. And in the end it’s mainly in very data-intensive environments that AI often comes into play.
In the customer-facing perspective AI is also rising in self-service e-commerce, order placement (and taking), customer service and contact centers, with automated customer service agents and so-called chatbots being examples. Yet, it’s still early days.
There is another customer-facing area, however, where artificial intelligence is starting to change the game through an increasing number of AI-powered cloud computing applications: sales. A deeper dive into the role, impact and usage of artificial intelligence in sales.
When asked about the role AI is poised to play in sales, Nancy Nardin from socialsellingtools.com pointed at the potential of AI and machine learning to help salespeople in sales productivity and prioritization.
If there is anything that AI can be useful for, it is indeed the augmentation of our human capacities to filter information and come up with the information that helps us do our jobs better and faster, often with a focus on taking over repetitive tasks and a predictive capacity that enables us to detect opportunities and patterns faster and in more ubiquitous ways.
Obviously, predictive capacities require mature technologies. When we say that artificial intelligence is becoming mainstream in digital marketing and other customer-facing functions we do include the types of AI that are mature and often used without really realizing it (social sentiment, automated ad placements, lead scoring, you name it). What we notice is that companies who used AI for, let’s say predictive scoring, like to embrace the artificial intelligence label again all of the sudden. When we look at AI in sales in this article however, we mainly mean those subsets of AI where important changes have been made in recent years and even months, realizing not all is equally mature.
Artificial intelligence and salespeople: the difference between selling and taking orders
Many observers focus a lot on artificial intelligence as a replacement for salespeople. It partially has to do with our science fiction visions when we start talking about artificial intelligence and with the idea that AI applications such as chatbots really have the potential to deal with an increasingly complex buyer and seller reality.
And it most certainly also has to do with the underestimation of B2B sales and buying evolutions. Sure, chatbots can further evolve and replace ordering systems. But sales is not about just taking orders of course.
On the other hand, back in 2015 Forrester did predict that by 2020 one million B2B sales jobs would be eliminated in the US, mainly to self-service e-commerce which would then account for 20 percent of the B2B sales force. Yet, Forrester too pointed out that order takers would be most affected.
Moreover, we need to distinguish between the different types of products, services and so forth that are sold as B2B obviously is a pretty broad umbrella and there is a difference between, for instance taking orders for office supplies and a consultative selling approach in complex and mission-critical IT systems, to name just two examples. Whether those numbers turn out to be true or not remains to be seen as well. For people who want to start a career in sales it might be a warning about the more interesting markets and desired skillsets though. If we look at the volume and variety of data that can be leveraged for sales purposes, the improvements in technologies and the evolutions in specific types of AI with the types of use cases we mainly cover here, we’re inclined to see an important growth of AI in sales indeed but at the same time think that 20 percent might be an overestimation. Lots of the newer AI technologies in self-service e-commerce (which we don’t cover here) are still far from mature.
Unfortunately we don’t have a crystal ball and it’s really hard to predict how AI and bots will impact employment in sales. Attitudes regarding AI and work do change and in the end the customer also calls the shots of course. If I want to engage with a sales person, I don’t want to engage with some virtual agent. What it will be tomorrow? It depends. Of course organizations want to automate a lot but it’s not because it’s possible that it’s feasible or even succesful. Our bet is still on augmented intelligence in sales. But, honestly, we don’t know.
Artificial intelligence and salespeople: the difference between replacement and augmentation
Regardless of these and other predictions it’s clear that AI (and robotics) will change the face of sales but, as usual, at different speeds, depending on the type of artificial intelligence, company, industry and certainly also sales AI use case.
AI already has started to change the game, not in the least because of vendor dynamics: sales is where the money is made, which isn’t too bad if you look at it from an AI solution vendor perspective. ROI and gains can rapidly be calculated as you’re close to the source, making the sell easier in a business function that is crucial for each organization. No wonder that AI is rising fast in sales in areas with matured, maturing and often drastically improved AI technologies.
And by the looks of it we’re indeed mainly talking augmentation rather than replacement here for now. So, when seeing all those messages on how AI will replace salespeople we can only think about the words of Peter Schwartz, SVP Strategic Planning at Salesforce: “I’d be more worried about being replaced by another salesperson who is empowered by intelligence than by a machine.”
That pretty much nails it. Augmented intelligence helping salespeople being more knowledgeable and empowered to be more productive and of course effective.
Einstein and geniuses: artificial intelligence in the sales cloud and beyond
A sign of the acceleration of artificial intelligence in sales and a reason we quote Peter Schwartz, in fact is Salesforce. The SFA and CRM giant announced a new platform in April, 2017, called the Salesforce Einstein High Velocity Sales Cloud.
If you encounter words such as Einstein and Genius in technology these days you can be pretty sure it’s about AI. Just think about how that other giant, IBM, held an event earlier 2017 in its Munich Global Watson IoT HQ, called Genius of Things, and covering the Internet of Things with an AI/cognitive twist and its Watson IoT Platform.
Who comes to mind when you say Genius? Indeed, Einstein. Salesforce already has an IoT Cloud Einstein, a Sales Cloud Einstein, a Marketing Cloud Einstein, a Service Cloud Einstein, an Analytics Cloud Einstein and so forth.
In the Sales Cloud Einstein we encounter typical AI-driven sales productivity enhancement possibilities such as opportunity insights, automated activity capture and, probably best known, predictive (lead) scoring. Salesforce’s Einstein clouds were announced and introduced end of 2016 and the company certainly isn’t the only one offering AI solutions for (among others) sales teams.
With the introduction of its Einstein High Velocity Sales Cloud, however, the company adds more AI and connects sales solutions with additional levels of AI within a single platform.
The reason we mention Salesforce obviously has to do with the position of the company in the market. We haven’t checked out Einstein High Velocity Sales Cloud but by the looks of it this time it might be more than adding the once again hot term artificial intelligence to features that already existed, with predictive lead scoring being one of them.
Key benefits and impacts of artificial intelligence in sales and sales management
If you look at all the AI-driven or AI-enabled sales tools out there and the ways they are used the two main areas where sales gets impacted revolve around 1) the automation of repetitive, mundane and less value-generation tasks and 2) the use of AI to, let’s put it simply, know more to sell more, faster and better.
Some tools simply connect with the CRM, some are embedded in the CRM (the Salesforce way) and some want to transform the CRM and seller experience entirely.
Yet, the growing entrance of artificial intelligence sales tools player besides the big existing CRM vendors and the rise of AI in sales as such doesn’t just impact salespeople and seller experiences or sales productivity; it also impacts the role of the sales manager. In fact, it impacts the future skillset of many managers.
End 2016, an article in the Harvard Business Review pointed out that, based upon research, successful managers will, among others, 1) need to leave administration to AI, 2) need to focus on work that requires human judgment, 3) foster collaborative creativity in their teams, embedding design thinking, and 4) develop the social skills needed for coaching, networking and collaborating as AI takes over many of their administrative and analytical tasks. We’re certainly not at the peak yet but you can start preparing.
The usage of artificial intelligence and the need to be more human in sales (management)
There is more but in a nutshell one could say that managers, including sales managers, and in fact even salespeople and knowledge workers, as the managers of themselves (responsibility) and of customer-oriented (inter)actions, including selling, in the end will need to focus on the human capacity of being…human and social beings that can inspire, teach, judge, motivate, convince, trust and help.
Isn’t that ironic in a sense? And isn’t part of this all, from the teaching part to the capacity to connect and convince by being knowledgeable, what modern sales and commercial theories want salespeople to do? The understanding of the customer beyond the direct understanding of the relationship between ‘them and us’, the teaching, the questioning and challenging (‘the challenger sale’), the consultative approach?
Artificial intelligence can only do so much (and that so much is a lot on the longer term) in sales but in the end it’s enabling modern salespeople to be better salespeople and modern sales managers to be better managers.
What can artificial intelligence help us achieve in sales?
So, artificial intelligence in sales has an important but very specific role as we see in the solutions and actual usage of AI in sales.
We’ve mentioned some of the benefits (and potentially negative consequences) as well as some things artificial intelligence can help us do in sales.
Summarizing and expanding a bit, artificial intelligence in sales can, among others:
- Help in predicting/seeing where sales revenue and closing potential is most likely; yet in the end it’s up to a sales rep to judge, for now.
- Help in mining and going through all those actions and activities and messages in the big integrated sales and marketing effort puzzle to detect interesting prospects and opportunities.
- Enhance sales productivity by removing those administrative and repetitive tasks as tackled before. Of course it’s up to salespeople to stop hiding behind the ‘we have too much to do’ as well.
- Help close the gap between marketing and sales, certainly in lead scoring where, as Nancy Nardin reminds us, we often don’t even speak the same language on MQLs. This isn’t necessarily a benefit of AI but it does come as a requirement if you want to use one of those larger AI solutions for sales and marketing where integration in many areas is key.
- Increase overall sales ‘intelligence’ and insights by not just going through all kinds of customer-oriented actions and activities but also getting faster insights in trends that will lead to market opportunities. Here’s an illustration of the latter: years ago we tried to convince several firms to build a solution and partnerships around EU GDPR compliance. For several reasons none saw the opportunity, had the time and so forth. If we wouldn’t have started doubting and convinced one company to move they would now be on top of Google search for GDPR, GDPR solutions and GDPR compliance, for starters. Imagine if we had a tool that could predict the market potential at that time (it was a good lesson in not doubting though).
AI in sales: does it pay off?
Does using artificial intelligence in sales really pay off (today)? Again the old consultant answer: it depends.
If you’re using an established platform for sales that adds AI features which are easy to use and provide clear benefits in reducing seller burden and increasing sales intelligence it does.
If you go for one of the several platforms which actually use more advanced forms of AI, serve a clear optimization goal and reliably work with reliable technologies and reliable data (in the end what it’s about) it shouldn’t be that hard either if you focus on what can really be done today and how you need to do it, apart from the hype. But there’s more in that stack and there are all sorts of solutions, certainly if we add bots and such in the equation.
In a June 2016 article in the Harvard Business Review, three McKinsey experts wrote about the rise of AI in the sales field. They confirmed the trend of a movement of buying to automated bots (15-20 percent already being sourced through e-platforms).
However, that’s not really our focus here as we look mainly at the B2B seller side. In research, conducted for their book Sales Growth (published in April 2016) the authors cite some pretty significant gains made by early moving companies in the adoption of AI in sales. An increase of over 50 percent in leads and appointments and call time reductions of 60 to 70 percent, to cite some numbers, isn’t nothing. But again, what were the platforms and cases?
What we do know is that in January 2017 MarketingDive wrote about Forrester Research data, indicating that marketing and sales combined account for approximately half of all AI initiatives but that spending is still relatively low. No idea what the portion of sales is, what types of AI investments we’re talking about nor which types of AI technologies and solutions are meant, let alone what are the AI use cases where the highest gains in sales are expected, which normally should be a driver of investments of course.
Artificial intelligence in sales in practice: some examples and solutions
In order to provide you with some ideas regarding how AI is effectively used in sales and can be used in sales (enabling you to find more benefits and maybe a solution for your needs), below are some platforms and tools for salespeople and sales (and marketing teams).
Note: this list is certainly not exhaustive. There are ample of people, companies and analysts who list, comment, rank and occasionally thoroughly look at AI sales tools. You find some links at the bottom of this article.
Conversica: your virtual sales assistant alter ego
Conversica is an AI platform that helps marketers and salespeople to detect the most qualified sales opportunities, using a 24×7 virtual sales assistant and intelligent lead engagement, messaging and identification. It can be used in conjunction with various other platforms (CRM and so on). The SaaS AI company already raised over $55 Million in total, the majority ($34 Million) in December 2016.
Conversica is mainly for larger businesses (or for high-value deals). Nancy Nardin mentioned it in our interview, calling it “a virtual (as in non-human) assistant that reaches out through email to trade-show and other lead lists to facilitate meetings with salespeople”.
Nancy ranks it in the ‘Prospect & Customer Engagement’ section of her Top Sales Tools of 2016. The concept of a virtual sales assistant is taken pretty far with Conversica. By giving the assistant a name, work hours and so forth it’s as if you have an additional worker persona.
Insidesales.com: from opportunity scoring to predictive forecasting
Insidesales.com is also for larger organizations instead of the individual rep and is a so-called sales acceleration platform.
It uses a predictive and prescriptive self-learning engine. Features include sales communications, opportunity scoring, lead scoring and prioritization, email and Web tracking, predictive forecasting and gamification. Data-driven prioritization and efficiency are really the keywords.
Helping sales teams sell more by disrupting the ways they sell is the credo. Predictive analytics is another keyword in the company’s approach.
Salesforce Einstein High Velocity Sales Cloud: AI in the sales process and CRM
We can’t overlook the earlier mentioned Salesforce Einstein High Velocity Sales Cloud. Pricing depends on the features you want and are affordable for pretty much everyone.
With this platform we’re in a somewhat different territory and should keep the CRM aspect of Salesforce in mind as well as features that already existed. There is lead prioritization/scoring, sales productivity enhancement (as anywhere else), automation of sales activities, trends identification and AI in several aspects of the sales process, within the Salesforce environment.
Lead scoring, higher conversions and win rates and productivity are keywords here too.
Tact: bringing the power of AI and CRM to voice and touch
Tact promises to transform the seller experience. How? With an AI-powered smart assistant.
Tact is different from the other tools we mentioned thus far in the sense that it uses AI to change the experience that salespeople have with their CRM (it’s on the Salesforce appexchange).
It’s mainly about interacting through voice (command), touch and mobile without having to log into the CRM and automating a series of tasks. Tact works with Amazon Alexa (Echo), iOS and Android phones and a range of apps and tools such as LinkedIn, Outlook and so forth (the other mentioned platforms connect with other platforms too). Tact might remind you a bit of the Salesforce1 mobile app but is different, by integrating more, offering a native app and being functional online. The makers call it device-native conversational assistance.
Gong: improving sales call efficiency and coaching
AI is also used in sales platforms and tools with a specific goal. Gong is a great example of this. Calling itself a conversation intelligence platform for sales, Gong essentially analyzes the calls and demos your salespeople conduct.
It records, transcribes and analyzes them, enabling sales reps to review their calls and those of others. Typical application: coaching and sales call efficiency improvement.
When we talk coaching and efficiency management in the context of a large number of calls (you can’t hear all calls without a tool) which are recorded, transcribed and analyzed when and where needed we obviously also talk about sales management that gets a better look into how calls are conducted. The human element comes into play here as well as Gong can be used in many ways: in sales team meetings with sales management and/or coaches, for individual call reviews, in peer-to-peer situations and so forth. While you might thing of AI sales tools as full automation, we can’t but repeat that the best tools out there are enablers of solutions to real-world challenges where the aspect of data volumes and analysis and/or better experiences and/or better productivity are nearby. A clear benefit and ease of use make all the difference.
More resources with applications that show AI at work in sales
As mentioned, there are far more sales applications using AI for various purposes, including some that are easily affordable for individuals who want to enhance a specific task.
And as promised, below are some sources where you can find more AI-enabled sales apps whereby you can see the reality of AI in sales in action, rather than just all the predictions. We mainly look at those that list tools with good potential, although it all depends on what you seek and how relevant it is to your individual and/or business context.
CB Insights: 10 AI sales companies and applications to watch
CB Insights offers a list of 10 companies using AI for sales purposes (published on March 8, 2017).
On top of Conversica, Tact and Gong they include Aviso (mainly predictive analytics), Takt with a k (AI for customer experience), Cogito (AI and behavioral science at the service of real-time guidance regarding phone conversations), Chorus.ai (also mainly in the conversation intelligence sphere), DigitalGenius (AI for the contact center), TalkIQ (conversational intelligence) and Altocloud (predictive analytics and increasing inbound sales velocity).
Constellation Research: sales productivity tools
Constellation Research has a report, the Constellation ShortList™ Sales Productivity Tools.
It is published in March 7, 2017 and you can access the shortlist of 5 solutions (on a total of 20) for free.
The solutions need to meet several criteria to be shortlisted, including the delivery of relevant prospect and customer insight to sellers and automated CRM activity capture to name just two. Tact is in the top 5, along with 4 we haven’t mentioned: Accompany, Komiko, Outreach and ToutApp.
Inc.: 5 AI-powered apps for individual sales reps and specific tasks
A last list you might want to check out (there are many more) is made by Bubba Page and published on Inc.
It dates from April 2016 and the reason we mention it is because, although the list mentions players such as InsideSales.com and Conversica, it mainly looks at 5 AI-powered sales apps that are more fit for individual sales reps and in some cases are free.
Moreover, they show other possibilities of AI for sales such as the right wording for emails to prospects or an AI assistant that takes care of scheduling meetings (no more emails back and forth). The platforms are x.ai, Spiro, Clearbit Connect, LeadCrunch and Chrystal. Useful or not? Up to you to decide.
That’s about it for now. It’s clear that AI is becoming key in sales too and that the main focus is on productivity, tackling real challenges and enhanced knowledge and ‘intelligence’ in order to simply be more effective. For now.
Disclaimer: we have no commercial or other relationships with any of the firms and solution providers mentioned in this overview of artificial intelligence in sales. Top image: Shutterstock – Copyright: Billion Photos – All other images are the property of their respective mentioned owners.