Today’s guest blog post is written by Gabe Larsen, an international sales consultant with over 15 years experience.
Artificial Intelligence is one of humanity’s most inspiring quests. I feel lucky to live in a time when there is so much initiative around Artificial Intelligence, and entrepreneurs are backing AI software development, recognizing it as a technology of the future. With all the talk around AI however, it’s sometimes hard to separate the wheat from the chaff. Real AI is supposed to drive real results in business growth – not just buzz and social media likes.
The CBInsights Top 100 Artificial Intelligence names some of the companies driving real results with Artificial Intelligence in businesses large and small.
InsideSales.com is in good company in the Sales and Marketing category of this list with companies like Conversica, Invoca, Amplero, Afiniti and Gong.io.
Even though there is so much excitement around the concept, research shows there is some mistrust as far as AI is concerned. While 55% of consumers have used AI in their personal lives, only 36% say they have experienced it in the workplace, and only 19% trust it for automating the sales process, according to “The State of Artificial Intelligence”, a study detailing attitudes and public perception towards AI.
The Path to Artificial Intelligence
In the sales industry, we chart the path to Artificial Intelligence based on the results you can achieve after implementing the technology.
Step 1: Data, and Lots of It
The journey starts with the data used for machine learning models. Most companies will have data and pride themselves to use it as base for sales and marketing activities. However, data is usually siloed, not easily accessible, or ‘dirty’–what we call unreliable data. This is all the more true in B2B or enterprise environments, where IT leaders are stuck with legacy systems, lots of technical debts and are riddled with compliance constraints.
The B2C space does not have this dilemma – they have billions of data points they can use freely and analyze to make the best decisions on sales and marketing. This is why companies like Amazon, Google, Apple and Netflix are successfully using AI to improve their user experience – and we know UX is a win on its own.
I have two good news for you here:
- One, data can produce useful results even when it is not ‘pristine’ – AI can still help, even if part of your data is not accurate.
- Two, you don’t have to rely on your own little pool of data. The magic is called crowdsourcing– and companies have been using it for some years to solve the problem of algorithm accuracy. Data is pooled from different sources, anonymized to ensure privacy, and then analyzed to find patterns of success.
Just by digging into this cross-company data to see what sales reps are doing, which are the most successful sales activities and which are redundant, the sales industry can increase efficiencies and productivity by 10%.
Step 2. Ideal Buyers and Sellers
Profiling your buyers and your sellers – and figuring out the ideal patterns for a successful sale can increase sales revenue 20 percent. Applied to buyer and seller profiles, AI can answer questions like:
- Who are my buyers? What’s their industry, geographics, title level, firmographics and other characteristics?
- How do my buyers prefer to be contacted (email, phone, social media or other) – and when, in which part of their day?
- Who are the best sellers, and what exactly do they do to close the deal?
- What’s their tenure with a company, what is the cycle of their pipeline and their ability to produce new opportunities?
Answering all of these questions, you are closer to finding the key to generate more pipe and increase sell rate.
The secret sauce is when you add external data to this equation. Stock data, investment announcements, acquisitions, or even whether it’s raining outside or not – all these factors can influence the outcome of your sales process. Imagine if you had all this at your fingertips.
Step 3. Custom Artificial Intelligence
I know, I know, this is the most frustrating thing you can hear from someone, if you ask: “Well, what can Artificial Intelligence can do for me, in my business?” — Well, it depends.
But bear with me now. On the ground, the reality looks like this: companies that are trying to implement Artificial Intelligence sometimes operate on international markets, have a complex portfolio of products, a diverse workforce scattered in multiple offices around the world, and deal with different compliance constraints.
The cherry on top–they all do not have the same selling processes, and the market-product fit is not the same for everyone.
So, if you think I’m avoiding this question– I’m not.
Artificial Intelligence has the potential to answer tough business questions about customer loyalty, attrition, up-selling strategies or product/market fit. It already has, in many companies, and it can mean a lift in revenue of up to 30 percent. However, the only way it can do this is with solid model analysis and input from data scientists.
I believe Artificial Intelligence is not here to replace humans, it’s here to amplify our efforts to create business value.
What Should an AI Do for You in Sales and Marketing?
There’s a sleuth of AI applications out there, like AI-driven marketing automation platforms, conversation intelligence platforms, AI-powered virtual assistants or business intelligence. If you’re considering adding Artificial Intelligence to your business, I beseech you– look into the real thing.
AI cannot be just a abstract concept, it has to produce real business results.
What’s your ROI for AI? Share your thoughts in the comment section below.
Gabe Larsen is Vice President of InsideSales.com Labs, the research and best practice arm of InsideSales.com. Labs works to uncover insights in the sales industry which help sales reps close more and bigger deals, faster, and using machine learning technology in the process.