Management consultant, educator and author Peter Drucker once declared that increasing the productivity of knowledge workers was „the most important contribution management needs to make in the 21st century.“
AI is changing that. More than 75 percent of companies are firing up AI to accelerate business development, automate busy work and deliver a better customer experience.
AI algorithms are powering massive amounts of calculations and decisions because they can find patterns in data, unseen to the naked eye. They’re evolving technology in powerful ways that are enhancing our knowledge work:
1. Automating the work humans don’t want to do
The most liberating support comes from AI doing the jobs we find monotonous. AI platforms can do repetitive tasks, like learn how to automatically update contact data in your customer relationship manager (CRM) or generate weekly status reports for your leads.
In the business development world, AI and machine learning tools sort through leads and pull a wide range of data together about your prospect list. The tedious work of organizing contact information or researching prospect demographics can be handed to bots and allow your sales team to focus on selling.
2. Automating the work we can’t do
How many hours per week do you need to focus on selling to meet your quotas and keep the business growing?
You probably don’t have hundreds of hours left over for data science. But, that’s what it takes to review large data sets to find trends in your industry, uncover business opportunities and stay ahead of the competition. Whether you want to know which companies are actively searching for your solution or how qualified they are, the data is available — but it’s complex and spread out across multiple websites and databases.
AI bots and services can look at how many pieces of content are being shared around a topic, determine traffic volume, number of companies searching for your product/service and their lead score.
AI can also deliver complex data sets to be reviewed on one platform, instead of having your team sort through thousands of lists or records. It can review and mark this data, then provide a report of actionable insights.
3. Improving lead quality and shortening sales cycles
A full pipeline isn’t useful if the leads aren’t relevant or qualified. Today, many companies use a variety of people and tools to do basic data entry before these leads are delivered to a salesperson. Even then, they’re only guessing which leads will be interested.
Sales teams that use predictive analytics spend less time prospecting and more time selling, which motivates them and makes them more successful in their role. This reduces sales department churn.
AI is the new go-to partner for this relationship. Algorithms can now score leads based on key performance indicators (KPIs) and historical success patterns. The closer a new lead matches your existing best-value customers, the higher AI can score it.
Delivering a flow of the best leads who are ready to buy can significantly reduce your sales cycle times. It gives you more revenue opportunities because your team isn’t overwhelmed with prospecting or follow up — they’re focused on selling to qualified opportunities.
Focusing on the people already looking for your solution provides a more enjoyable process for both you and your future customer.
4. Predicting cross-sell and up-sell opportunities
AI provides a connection that we weren’t expecting initially but are pleased to see: people who want the advanced services our sales team can offer.
p-sells and cross-sells are often missed because sales teams lack a definitive process for whom to up-sell and when. It’s the easiest and most neglected part of the sales process.
AI makes your sales process more predictable by finding the customer personas who are most likely to say yes. That ensures sales teams are focused on customers with the largest revenue opportunity and the highest likelihood of converting.
Advanced analytics can help create these personas, and the AI underneath it can continuously update those personas based on how successful its past model was. Buyers enjoy the help. Businesses enjoy the increase in revenue. And sales teams enjoy hitting those stretch goals and maximizing their bonuses.
5. Forecasting sales projections for specific customer personas and offers
International Data Corporation (IDC) notes that real-time personalization of ads will arrive by 2020. The goal for these platforms is improving the accuracy of targeting, increasing the precision of its messaging and ensuring the context is appropriate for the customer and their pain points.
Smart AI will power these platforms and we can start to see it bridging the gap between inbound marketing and outbound sales development — aligning sales and marketing once and for all.
When we look at the possibility: It’s targeting your best customer personas with the best messaging to analyze buying stages, marketing channels and optimize them all. In essence, we’re learning the personas that respond best to each offer and when up-sells correlate with an increase in churn.
It’s possible for AI to scan an entire integrated database, from CRM and customer orders to conversation intelligence and lead scoring tools. Machine learning can build out customer personas that include risk prediction and sales potentials, segmenting groups into a variety of characteristics.
It’s a nuanced understanding of the customer journey that takes a few extra things into account:
- Customer lifetime value
- Risks relative to sales thresholds
- Intervention points for sales and support
- Projections by category and product type within customer groups as well as individual customers
This greater understanding can be used to guide a variety of business decisions. Initially, companies can use it to manage pricing and sales strategies. Later, there’s a clear understanding of messaging success rates by persona and product needs — even the potential for a tailored customer journey with offers designed to maximize revenue, while minimizing churn.
6. Making human work more meaningful and valuable
AI in business development boils down to this: It gives us the freedom to focus on our unique abilities. We’re not bogged down with repetitive busy work or boring data entry. We can focus on the meaningful work — the elements that lead to a successful sale and customer experience.
AI runs in the background and gives us the ability to increase the productivity of knowledge work.
„Every few hundred years throughout Western history, a sharp transformation has occurred,“ Drucker observed in a 1992 essay for Harvard Business Review.
In a matter of decades, technology altogether has evolved at light speed — its purpose, applications and capabilities. Years later, AI is changing our work in meaningful ways. And the people entering this brave new world can’t imagine work without this valuable tool. AI is transforming technology, saving us time and uncovering new sales opportunities — and surely exceeding the expectations of Peter Drucker.
Source: Mark Marcelletti