Automated and Amplified: Sales Meets A.I.

Sales is evolving. Predictive and powerful, it’s no longer just speed that separates the best from the rest – it’s processing power. Today’s strongest sales engines are not only blisteringly quick – thanks to A.I. they’re now intelligent.

Consider the research:

• By 2020, 30% of companies will use AI in at least one of their primary sales processes. (Gartner Predicts 2017: CRM Sales)
• By 2020, insights-driven businesses will sap over a trillion USD per year from their less data-driven peers. (Forrester Predictions 2017: Artificial Intelligence Will Drive the Insights Revolution)

Why AI? To better optimise and prioritise

Consider a salesperson’s typical day: prioritise leads. Nurture some. Close others. Trawl customer data for new prospects. Send a follow-up email. Personalise a pitch…

At core is this: working out how best to spend the next chunk of time, when there never seems to be enough of it.

It’s a classic game of optimisation: working out how best to deploy resources – in this case time, energy and focus – in a resource-constrained environment.

So, optimisation is where it’s at. But here’s the kicker: the human brain isn’t all that good at optimising, particularly in data-dense environments.

And here’s the fixer: machines are great at it.

Using A.I. to simplify

Given the massive amounts of data salespeople need to draw from when both searching for new leads and managing existing accounts – data covering everything from business and personal details to buying histories and account statistics – getting machines to do much of the grunt work makes sense.

And it’s why many companies have already tapped into the abilities of A.I., in turn remaking how they approach the sales process.

5 ways AI can improve the sales process:

1. More accurate aim. A.I. is able to isolate the products, services and solutions that will best meet a specific customer’s needs with extreme accuracy. The input comes from data – a growing amount of it. Everything from internal customer records, customer interactions and a rising number of external sources yield the information needed to make suggestions and interactions more meaningful.

2. Superior speed. Real-time customer buying behaviour can be analysed by A.I. in order to refine its algorithms, meaning audience targeting stays dynamic. Moreover, admin is reduced. By automatically capturing the right data from email to populate CRM records, there’s less of a  need for manual updating by sales staff.

3. Better insight. By monitoring communications to and from a customer, A.I. is able to assess the health of that relationship. This allows salespeople to put in time where it matters most. And forcus on deal most likely to close.

4. Improved prioritisation. Analysing thousands of leads is an impossible task for time-poor sales teams. AI is able to identify which lead might benefit from a follow up email, specific pitch, or relationship nurturing – cutting through the complexity.

5. Better personalisation. The interactions that produce the best results – be that in terms of deal size, increased loyalty scores or customer satisfaction – are personal, tailored and above all relevant. In the digital age, customers expect personalisation as a given. By drawing on background data, A.I. is able to make targeted recommendations.

Microsoft Dynamics’ next-level A.I.

Over the last couple of years, Microsoft has been upgrading every node in its Azure cloud platform. This multibillion-dollar investment now allows Azure to run a host of A.I., cognitive computing and neural networking-based applications.

The result is that Dynamics 365 Enterprise Edition brings together Microsoft’s customer relationship management suites and infuses the entire platform with new, advanced AI capabilities.

Two new stand-alone A.I. apps are also debuting as part of the Dynamics 365 Enterprise Edition: Customer Insights and Relationship Insights. These apps leverage the power of Azure machine learning algorithms and Cortana predicative intelligence to bring new insights to data, whether that data is in Dynamics 365 apps or Office 365.

To find out more about A.I. and supercharging your sales process, check out our Microsoft sales solution.

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Smart Talk: How artificial intelligence is reinventing customer service

The companies that get it right reap the rewards. Consider the stats:

• Research shows that 9 out of 10 consumers are loyal to brands who offer low-effort interactions.¹
• More than three-quarters of global consumers hold a more positive view of brands that provide proactive customer service notifications.²

To keep customers engaged, however, companies must compete in a marketplace where the benchmarks keep rising. Why? Exposed to the offerings of best-in-class digital juggernauts such as Amazon, consumers develop a taste for the most cutting-edge tech – and soon come to think of it as normal – whether they’re aware of it or not.

What are the drivers? A major one is advancement in AI. Today, artificial intelligence underlies an increasing number of customer service interactions – at both the front and back end. From brand spokesperson to service agent assistant, AI is remaking the interface between brands and their customers.

ow? Here are some of the ways.

AI is many customers’ first touchpoint.

Many of today’s consumers would rather find a solution to a query without having to dial into a call centre or deal with a service agent over the phone. Brands know this, and it’s why chatbots are an increasing number of brands’ first line of contact.

Easily accessible via a messenger window, bots are great at dealing with simple and medium-complexity queries. The result is quick customer resolution as well as decreased workload for the company’s human agents – to whom a bot might refer a customer in the case of a complex query.

By filtering incoming queries in this way, companies are realising that a human touch isn’t always necessary. Rather, it’s efficiency that customers want.

AI – which is able to draw on a range of data spanning past brand interactions (and often external data, too) – isn’t working from a blank slate. Rather, it’s able to contextualise queries, making sure replies are targeted, helpful and to the point.

AI is flexible.

Today’s customers take digital dynamism for granted. Daily immersion in tech means multi-device connectivity – and interaction on their own terms. For many, their nearest bank branch is an app. Their nearest retail outlet, their mobile. Brands have to keep pace. Access to a device means access to AI, whether via a messaging app or website.

AI is predictive.

Consumer queries are rarely totally unique. An issue or question raised by one customer is likely to soon be voiced by another. AI comes into its own in this area.

On one hand, when the same query is raised by a number of consumers, AI begins to learn. By piecing together the reasons behind a specific type of query, AI can learn to provide more helpful and targeted solutions to subsequent customers – having found what resolution worked best for those who came before.

More importantly, AI is able to predict queries before they happen. Through IoT-enabled devices, weather forecasts, inventory management services and more, AI can now anticipate when a customer is likely to call in, and why.

The result is the ability to pre-empt queries and surprise customers with helpful suggestions, at just the right time.

Building Business Dynamism

Microsoft Dynamics 365 offers an embedded suite of advanced AI capabilities, capable of tackling complex scenarios end to end. Here are four ways:

1. Omnichannel engagement. A unified platform provides 360-degree customer views across devices, drawing on a full history of interactions, user preferences, and other relevant customer information, even from third-party applications.
2. Self-service and community access. Those who prefer to find answers on their own through self-service and community options can now do so – including accessing help via third-party sites, such as Facebook.
3. Agent empowerment. Agents are able to access a single environment on their desktop or mobile device, allowing for more personalised and meaningful customer interactions. Topic analysis and machine learning scenarios also bring up relevant articles at the right time, meaning agents are equipped to solve cases faster and improve first-time resolution rates.
4. Unified knowledge. A single source of knowledge provides approved content across channels and lines of business. Knowledgebase administrators can also capture and create content from multiple sources, while the approval workflow makes sure information is accurate and mitigates risk.

Want to find out how you can infuse AI into your customer service?

See our AI-enabled customer service solution.

¹ Shifting the Loyalty Curve: Mitigating Disloyalty by Reducing Customer Effort by the Corporate Executive Board (CEB)

² 2016 State of Global Customer Service Report, Microsoft

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