Artificial intelligence in B2B sales and how to use it properly.

AI technologies are all the rage in sales and chances are you’re considering them for your own organisation. But what is AI really and how can you avoid the five mistakes sales managers make when dealing with AI?

We’ll help you uncover our top tips for successful AI in sales with this 7-minute read.

What is Artificial Intelligence (AI) in Sales?

In simple terms, (narrow) artificial intelligence or AI is computer-based decision-making. It uses software to process huge amounts of data (more than a human ever could) and turn it into actionable insights. AI goes beyond simple data analysis to find and act on these patterns. Modern AI for sales and other applications does not strive to be like or surpass a human (that would be so-called “strong” artificial intelligence. This is science fiction). Rather, it is about creating systems that solve problems effectively and quickly.

How prevalent are AI technologies?

As a result of their utility and vast processing power, AI technologies are everywhere. They do everything from anticipating vaccine shortages to fueling predictive sales software that reduces customer churn, finds Cross-Selling and Pricing.

In fact, Gartner reports that AI rollouts are up 270% in the last four years and most organisations are planning even more projects involving AI technologies. The $97.9 billion expected spend on AI in sales and other applications in 2023 will drive an extra $15.7 trillion USD in additional GDP. In Germany’s retail sector alone, according to Market Research, “Over the forecast period (2019-2025), spend on AI is expected to record a CAGR of 21.8%, increasing from US$ 196.6 million in 2019 to reach US$ 783.3 million by 2025.” That’s because AI technologies like predictive sales software help cut costs, find new opportunities and improve loyalty.

What are the five mistakes sales managers make when dealing with AI

Getting a SaaS that doesn’t align with your business goals is one of the many errors that sales managers make when shopping for AI technologies like predictive sales software.

Be on the lookout for problematic mistakes like:

1. Lack of internal skills/resources to action

If you don’t have the right team to act on the recommendations from your predictive sales software, then you’ve fallen at the first hurdle. It’s no use for AI in sales to tell you what to do to generate more revenue and retain customers if there’s no team to back it up.

2. Sales software that is not as it seems

Marketing teams can come up with some fantastic collateral with all the bells and whistles, but be on the lookout for AI washing. Make sure you know the full capabilities of any product that you purchase.

3. Software as a Service (SaaS) misaligned to ROI

It’s easy to spend thousands on a flashy product that won’t actually generate any results for your business. Make sure that all the extra integrations, features and support you’re paying for in your AI technologies will actually translate into business results. If you don’t have a bulk email system, don’t worry about your AI integrating with one. Don’t get excited about what software CAN do versus what you NEED it to do.


4. Legacy systems unclean

ERP, CRM and basic API connections are all possible with predictive sales software like Qymatix; making these systems smarter. But if your data is not in a usable format or poorly maintained, you won’t see the same level of ROI from your AI in sales that a competitor with a ‘cleaner’ legacy system would.

5. Cultural worries about AI support

Automation concerns and the rise of AI in sales have a number of people worried about job losses. If your organisation has a culture that fears change and avoids technology as a whole, then bringing in AI support will only cause more concern.

How to launch AI technologies successfully in sales

To avoid these five mistakes sales managers make when dealing with AI, you’ll want to:

1. Designate champions with ownership

From key stakeholders to frontline management with direct oversight of the predictive sales software integration; you’ll want to determine who is leading the implementation and who will nurture it so your wholesale or manufacturing organisation sees the benefits.

2. Align SaaS purchases to core business goals

Before you sign the contract, make sure you know what your use case for predictive sales analytics actually is. That way, you’ll be able to create SMART goals around the use of your new AI system and measure its performance against benchmarks.

3. Clean existing data

For any systems integrating with AI, you’ll want to standardise the input and ensure its accuracy so you get correct predictions. Also, try to avoid bringing in any data that’s subjective – like the personal notes from your sales team.

4. Define where AI will automate decision-making

To prevent being taken in by AI washing, make sure you know how the system will help you to make better decisions. Define the roadmap for when and where the AI in sales will hand over to its human counterparts.

5. Train in pro-AI sentiment

Launch learning programmes and align your values to help your employees see AI in sales as a great tool to help team members do a better and more effective job. Teach your staff that predictive sales software automates all those boring analysis functions so they can focus on driving revenue.

Five Mistakes Sales Managers Make when Dealing with AI and How to Fix them – Summery

The five mistakes sales managers make when dealing with AI are easily fixed with a bit of planning, goal setting, training and benefit-matching. If your organisation is interested in harnessing the power of predictive sales software to increase your earnings and cut costs, then let’s talk! Our AI-based Predictive Sales Software can make your ERP or CRM into a decision-making powerhouse that frees up time for your teams to close more deals and save existing contracts.


Further Read:

Sujai Hajela (2019): The Top Five Mistakes Companies Make With AI. Ed.: Forbes