Big data technology is incredibly important in many aspects of modern business. The sales profession is one of the areas most affected by data. Companies spent $2.8 billion on marketing analytics in 2020 alone. That figure is growing substantially each year. There are many ways that big data is helping companies improve sales. One of the biggest benefits is that it can help automate many aspects of the sales process.

Data analytics technology is becoming a more important aspect of business models in all industries. SaaS companies are no exception. They need to leverage analytics strategically to maximize their revenue. The importance of customer loyalty and customer service has become increasingly well-known and companies have needed to adapt their business models accordingly to gain a competitive edge. One survey found 83% of customers attributed their brand loyalty to the ability to trust a company.

News headlines everywhere scream fears of robots taking over jobs, creating an ever-growing pool of unemployable humans who cannot compete with machines. This concern, while understandable, is unfounded. In truth, Artificial Intelligence (AI) will arguably be the greatest job engine the world has ever seen. Both automation and AI underscore how central and critical human insight and expertise are to business success. And nowhere is this more evident than when we look at the impact of AI in the sales process.

The road from marketing-qualified lead to sales-qualified lead can be a long one, and it's a road that seems to have more exits than on-ramps. But this process can -- and must -- be sped up to increase your lead conversion rate. Instead of hiring beyond your plans and budget, consider how automation and AI don't get tired, they can't have too much on their plate, and they never get frustrated in the face of failure. The lead often doesn't even realize they aren't communicating with a flesh-and-blood salesperson when they're speaking to conversational AI. Lead conversion stalls due to slow follow-up on qualified leads -- but conversational AI automation can always respond briskly no matter the volume of leads.

These days consumers and businesses no longer think of artificial intelligence (AI) as something from a sci-fi movie or book – that's because AI is now part of everyday life. Just think of Netflix's suggestion algorithm, Uber's location algorithm and even Tinder's matching algorithm – all business models powered by AI to help drive consumer decisions. And the same AI can be used in the sales process to help sales teams make decisions. At World Tour Sydney Reimagined we saw Salesforce Einstein Voice provide deal coaching to sales reps using predictive technology. And in the Sales keynote, Modern Star explained how their sales reps were using data insights to further understand their customer and close deals.

These are just a few of the things that come to mind when we think about artificial intelligence (AI). AI is the buzzword that seems to be on everyone's lips. To some, AI signals a utopian future, while others foresee a dystopian nightmare coming to control us all. But before you try to ignore AI or run for the hills for fear your job is on the line, let's dig a little deeper. Fact: AI is transforming business operations and increasingly becoming our interface with technology.

In the previous article, we discussed the importance of having a chatbot for your sales channel. You can use chatbot to automate the lead generation process, fix appointments with qualified leads, or to even close sales for you. Whichever part of your sales cycle you choose to automate, it is important to plan the implementation of chatbot. Let us have a look at the steps involved in designing your sales bot. The first step to designing a sales chatbot is establishing a goal. It is important to have a clear purpose for the chatbot before setting it up.

As companies collect increasing amounts of data about customers, a key challenge is connecting that information to customize the customer experience and boost sales. The customer journey begins long before the actual sale. It starts with online searches, store visits, conversations and emails. Companies need to connect all of these touch points to identify potential customers and turn research and exploration into sales. While business-to-consumer (B2C) markets have been deploying customer data platforms to consolidate the customer experience and improve marketing personalization, this has been a bigger challenge in the business-to-business (B2B) markets.

It is Sales & Marketing Alignment month on SalesPOP! So continuing our series on artificial intelligence, let's now take a look at AI and how it fits in with Sales & Marketing Alignment. As we know by evaluating the current state of Sales & Marketing Alignment, it is still a major challenge to get these two groups working in unity. Yet in today it's vital that they do–if only because in today's digital marketplace it's getting more and more difficult to tell where exactly Marketing ends and Sales begins. Although there are clear opinions on the subject, we have never totally solved the question of lead generation being specifically a Marketing or a Sales activity.

Artificial Intelligence in business has become synonymous with a forward-thinking approach to all aspects of business strategy, from marketing to sales to finance. Many sales tasks that used to require team members to prepare spreadsheets and spend hours filtering and analysing data can now be streamlined by AI and automation. In this post, we'll explain how applications of artificial intelligence can improve sales team performance, show how AI software can change your team's relationship to the sales cycle - for the better - and we'll offer some notable artificial intelligence examples. When we think of AI, perhaps sci-fi movies and stories of the foundational research of Alan Turing still come to mind. However, in 2017, AI has become part of everyday business life, and its march into the business world shows no signs of slowing.