Artificial intelligence is a hot topic for many industries. When it comes to sales, the situation gets complicated. According to the latest Salesforce State of Sales report, just 21% of organizations use AI in sales today, while its adoption in sales is expected to grow 155% by 2020.
Let’s explore what keeps sales teams from implementing AI and how to overcome these challenges to unlock new opportunities.
Why do so few teams adopt AI in Sales
There are a few reasons behind such a low rate of AI application in sales. First, some teams don’t feel they are prepared to integrate AI into their existing strategies. Second, AI technologies are often applied in a hectic way: many businesses have high expectations of AI and concentrate mostly on its benefits rather than contemplating possible difficulties upfront. Such an approach rarely results in positive business transformation.
Here are some common challenges that businesses need to overcome to turn their sales AI projects into success stories.
Businesses don’t know how to apply AI in their workflow
Problem: Different industries call for different uses of AI. Still, companies tend to buy AI platforms to use them for the same few popular tasks, like predictions based on historical data or automatic data logging. In reality, the business type and direction should dictate what AI solution will best fit the needs of an organization.
For example, in e-commerce, AI can serve dynamic product recommendations on the basis of the customer’s previous purchases or views. Teams relying on email marketing can use AI to serve personalized email content as well as optimize send times.
Solution: Let a sales team participate in AI onboarding. Prior to setup, gain insight into your sales reps’ daily routine, needs, and pains. Then, get their feedback continuously during the actual AI implementation. Such a strategy will ensure the sales team benefits from a tailored, rather than a generic, AI system.
AI requires data businesses don’t have
Problem: AI is most efficient when fed with huge amounts of data. It’s true, a company with a few hundred leads per week will train AI for better predictions than the company with the same amount of leads per month. Frequently, companies assume they don’t have so much data or they cannot present it in a suitable format to train an AI algorithm.
Solution: In reality, AI can be trained with incomplete and imperfect data. Instead of trying to integrate the whole set of data prior to implementing AI, it’s possible to use it with data subsets, like historical purchase data or promotional campaign analytics. Plus, AI can improve the quality of data by predicting missing elements or identifying possible errors.
Businesses lack skills to manage AI platforms
Problem: AI is a sophisticated algorithm that requires special skills to implement and use it. Thus, sales teams need to be augmented with specialized knowledge in data management, software optimization, and integration. Otherwise, AI tools can be used incorrectly and thus provide little value.
Solution: There are two ways of solving this problem. First, it’s possible to create a new team of big data, machine learning, and analytics experts to run AI implementation and coordinate it with the sales team. This option is rather time-consuming.
Second, it’s possible to buy an AI-driven platform, like Salesforce, for example, that includes both out-of-the-box features as well as plenty of customization opportunities. Instead of hiring new specialists to manage the platform, you can reach out to Salesforce consultants who will help you select the best-fit plan, configure, and implement it. If your requirements go beyond the features available by default, then it’s possible to add custom functionality.
How AI can change the sales of tomorrow
When you have a clear vision of the AI implementation challenges and understand how to overcome them, it’s time to make use of AI-provided benefits.
A core benefit of any AI system is its ability to analyze large amounts of data across multiple platforms and then connect the dots, i.e. draw actionable conclusions. To illustrate these AI opportunities, let’s take Salesforce, one of the most popular solutions in this domain today, and see how its AI technology, Einstein, can enhance a sales workflow.
Time-saving and productivity boost
Administrative work eats up sales reps’ time that they can spend selling. That’s why many administrative tasks should be automated. Salesforce Einstein can save time usually wasted on manual data entry by:
- Automating contact creation and update
- Activity logging
- Generating lead status reports
- Syncing emails and calendars
- Scheduling meetings
Efficient lead management
When it comes to leads, sales reps tend to base their lead management strategies on gut feeling. In spite of its importance, intuition cannot be the only means of assessing leads. The approach should be more holistic. AI has unmatched abilities to analyze large amounts of information from different sources to help score and prioritize leads. In combination with sales reps’ intuition, such data can bring lead management to a new level.
For example, Einstein AI can help with:
- Scoring leads based on historical data and performance metrics of the best customers
- Classifying opportunities in terms of their readiness to convert
- Tracking reengaged opportunities and nurturing them
AI is well-known for its predictive capabilities that help sales teams make smarter decisions without running endless what-if scenarios. AI forecasting builds sales models using historical data. Such models anticipate possible outcomes of multiple scenarios common in sales reps’ work. Salesforce Einstein, for example, can give the following predictions:
- Prospects most likely to convert
- Deals most likely to close
- Prospects or deals to target
- New leads
- Opportunities to upsell or cross-sell
The same algorithm can be used for forecasting sales team performance during a specified period of time and taking proactive steps based on those predictions.
What’s more, sales intelligence is shifting from predictive to prescriptive, where prescriptive AI does not recommend but prescribes exact actions to be taken by sales reps to achieve a particular outcome.
Watching out for pitfalls of AI in sales
While AI promises to fulfil sales reps’ advanced requests, there are still some fears and doubts around it.
First of all, as a rising technology, AI still carries ethical issues related to its safe and legitimate use in the workplace, such as those of the integrity of autonomous AI-driven decisions and legitimate origin of data fed to algorithms. While the full-fledged legal framework is yet to be worked out, governments have already stepped in. For example, the High-Level Expert Group on AI of the European Commission came up with the Ethics Guidelines for Trustworthy Artificial Intelligence covering every aspect from human oversight and technical robustness to data privacy and non-discrimination.
In particular, non-discrimination relates to potential bias,, such as algorithmic bias that comes from human bias when sourcing data, and the one where correlation does not equal causation. Thus, AI-driven analysis should be incorporated in decision-making cautiously as just one of the many sources of insights. AI won’t replace a human mind—the data still needs to be processed critically.
When it comes to sales, another common concern is that AI will take sales reps’ jobs. Yes, some tasks that are deemed monotonous and time-consuming are indeed taken over by AI automation. However, it is actually a blessing as AI does not replace jobs but augments them. This way, sales reps can have more time on their hands to complete more creative and critical tasks.
It’s true, however, that employers would need people who know how to work with AI technologies. It means either ongoing training or new hires, which can be rather costly. The stakes are high, though. To keep up with the fast-changing world, one has to bargain their way to success, finding one’s way around current limitations and challenges.
In a nutshell
AI is key to boosting sales team performance. However, successful AI integration into sales and marketing strategies requires teams to overcome challenges posed by sophisticated AI technologies. Such popular AI-driven platforms like Salesforce help sales reps get hold of the AI potential as well as enjoy vast opportunities for saving time and increasing productivity.
Valerie Nechay is MarTech and CX Observer at Iflexion, a Denver-based custom software development provider. Using her writing powers, she’s translating complex technologies into fascinating topics and shares them with the world. Now her focus is on Salesforce implementation how-tos, challenges, insights, and shortcuts, as well as broader applications of enterprise tech for business development.