You may be wondering why we’re taking a look at data analytics, artificial intelligence (AI), and machine learning (ML). There are two reasons. The first, simple answer is that it would be silly for any business not to use the power of technology these days to help them make two types of important decisions:
- long-term strategies based on data analytic reports, and
- agile adjustments using real-time data.
But there’s a much more crucial second reason now to use data analytics, AI, and ML. And that’s because user experience (UX) has become a top differentiator in business success.
It’s like this: It’s essential your prospect feels your brand is right for them, gets an enjoyable experience dealing with you, believes you’re addressing their pain points, and that it’s easy to do business with you. This is what leads to a close of sale and creates brand loyalty.
And your human sales reps are best placed to creatively offer your prospect this great UX at every touchpoint. They know how to imaginatively leverage the data you collect in order to take better care of your customers.
However, what about that huge list of routine tasks they have to deal with every day? Have you noticed it consumes them like the legendary Jaws?
McKinsey reckons at least 30% of sales tasks can now safely be automated. That’s why making full use of data analytics and automating your processes with artificial intelligence and machine learning are essential. They leave your reps free to carry out the creative customer-focused parts of your business strategy.
In this article, therefore, we’ll highlight the differences between these more robotic aspects, suggest some possibilities to consider, and offer three areas where your company can benefit from a greater use of this technology.
Using Technology to the Full
Your greatest business asset is your data. And because you can now gather data in such huge quantities, you should use them in every possible way to your benefit!
Data analytics heads the list. And within that topic, artificial intelligence and machine learning can go further and use these data in ways your brain probably can’t, and thus automate tasks. So let’s look at each aspect in turn.
Data Analytics
Basic data analytics means examining your existing datasets in order to gain insights, find trends in your sales, and draw conclusions about the information. Your human analyst can do it, of course, but artificial intelligence (a computer!) can do it better! Either way, your aim is to
- find answers to problems you need solving, and
- gain smarter insights in order to improve on already existing solutions.
Question: How might your business extend the use of data analytics to solve a new problem or throw light on a complex situation?
Artificial Intelligence
Artificial intelligence, as we indicated, is really a computer that’s programed to simulate the human intelligence and behavior of (for example) your analyst! But on a different, more complex scale.
AI can, for example, use your data to predict and forecast future trends in your sales that could offer an advantage to your business. Or examine past data and highlight deep sales patterns in different demographics. Or compare subsets of pricing vs. customer segments to help with planning.
The caveat here is that word “could”: When firms and customers take spontaneous decisions, it’s impossible to totally account for a mass act of spontaneity. But you can use data and AI and make better decisions as far as is possible!
Question: How might your business benefit in future from AI-produced insight from multiple past data sets?
Machine Learning
Machine learning is a subset of AI. It means you’ve given a machine the capability to automatically learn from past data and apply it going forward. Think how your phone learns not only any possible next word but the one you’re most likely to use from past experience of watching you type!
In this way, ML leverages your available business data to learn better from what it “sees.” For example, if a machine learns to read and understand the context of your incoming messages, your digital assistant tool can read emails, extract the essential information, and know to insert it into boxes on digital forms.
This is significant in business. You’re not interested in digital solutions for their own sake, only in how profitable they can be for you! Form-filling is tedious, time-consuming, and prone to errors.
Another example: Your finance department can use ML to peruse all available customer data and patterns, and flag up unusual events. It learns what is normal and therefore recognizes “not normal” – or possible fraud! A human can then investigate. ML has perhaps saved you money.
ML can also learn how your users interact with your app or social account, for example, and send targeted offers at the right time – perhaps when they’re in a certain place.
Question: How might your company introduce machine learning to improve notifications or customer service?
Note!
We’re not jettisoning humans! Not yet. They’re at the other side of the room working on creative ways to target your ideal customer in different channels – or engaging more deeply with your key accounts.
But in the meantime, the technology is bringing you other benefits. So let’s see what’s in it for you!
3 Ways Your Company Can Benefit
1 Performance
Integrating these technologies, even in a small way, will transform your business processes and increase your overall business performance. That’s because extracting relevant and specific data from the data lake (i.e. data analytics) is super-fast and helps you:
- Quickly respond to your customers with a central dashboard of information
- Solve internal problems by helping you see the bigger picture
- Improve your systems, based on insight gained
- Streamline outcomes across all departments – information is instantly available to act on
Think about it: Netflix and Amazon already have instant data to hand and use it well. They monitor deliveries and who is watching what in real time. It undoubtedly contributed to their sales growth before lockdown was even thought of! The consensus is that timely data gives you a competitive advantage.
2 Customer Experience
As we mentioned, you must now prioritize customer experience throughout their buying journey with you. Adopting AI/ML alongside analytics in your marketing efforts helps you meet customer expectations. So, what are these customer expectations and how do these technologies allow you to meet them effortlessly?
- They expect personalized interactions. AI/ML can help you personalize your offerings through gathering relevant customer insights from your customer records that you can use to improve their experience. (We mentioned targeted offers above.)
- They expect to engage in direct communication, and fast. You can’t be on duty 24/7. However, with tools like chatbots, digital assistants, and quick feedback portals, you can deliver information to a customer who asks, whenever and wherever. The tool can also offer to pass them to a human if they prefer! They mostly don’t.
- They expect you to be proactive. Don’t wait to interact with your customers only when they approach you. Show them you value them by offering helpful tips or educational materials through digital marketing. For example, when the AI notices your customer frequently browses a particular item on your website, the system can proactively offer them a discount. Your AI/ML tools choose the best channels to reach your customers with the right information.
3 Sales
Even with the best sales processes and marketing strategies, your company may not close as many sales as you’d like. However, this can change with the right AI/ML tools together with data analytics. Here are some ways they enhance sales:
- Sales forecasting. Using predictive data analytics models, AI/ML is able to go through your data lake, and analyze and understand patterns to make better predictions that will increase the accuracy of your plans.
- Automation of sales tasks. Your sales people will be able to close more deals and shorten the sales cycle because AI tools help them identify patterns, update information quickly, avoid prospects slipping through cracks, send sales funnel emails etc., and maintain a consistent process.
- Lead generation. This process has become quicker with AI/ML tools that monitor web traffic and possible customer opportunities, filter the most appropriate for you, and help your team know when and where to reach out.
How to Start Using Data Analytics, AI, and ML in Your Company
You probably already use some aspects of these technologies in your business operations. However, data-driven analytics are often underestimated. So let’s close with three ways you can realize the most benefit from them.
1 Pick the right use cases that will benefit your circumstances and resources. The size of your business will dictate which are essential rather than merely “desirable.”
2 Build a strategy to help you understand how AI/ML and data analytics will align with your business goals and objectives. You can then identify what tools will work best with your customers and target audience.
3 Partner with experts. If you’re not tech savvy in this area, it can be wise to outsource to a tech team to help you navigate the terrain in the best way, leaving you to be creative with the sales processes that humans excel at!
We Can Help You!
At Waterways, we’re always keen to help you grow your sales. Data analytics, AI, and ML are transforming the way our business world operates. Contact us today and let’s discuss how you can automate your sales processes with relevant technology and gain a strategic advantage in the marketplace.