You don’t have to be entrenched in the tech world to have heard the term, “artificial intelligence,” but what is artificial intelligence, or AI, as it’s commonly known? Simply put, AI is the simulation of human intelligence processes performed by machines or computer systems.
Nowadays, AI is being used to carry out many jobs previously held by humans, and while this concept may sound futuristic and even scary to many, there’s no need to panic. Most AI functions are designed to make life easier.
Whether you know it or not, most of us use AI in some form every day. Only 33 percent of people think they use AI, according to one study, but in reality more than 77 percent use some form of AI-powered devices or services.
For example, AI is used by most banks to personalize your experience on their mobile apps, while music services use AI to track your listening habits and then use that data to suggest other songs you may like to hear.
AI and Predictive Lead Scoring
As it relates to business, AI can be beneficial when used in systems and applications by automating repetitive, menial tasks that people used to do manually, thereby increasing company productivity and profitability.
More specifically, sales and marketing tools such as customer relationship management (CRM) software or sales automation platforms that contain AI technology not only can do simple, tedious tasks such as data entry, but also can identify patterns and trends in that data in just seconds, and tell users how best to use it.
With real-time information, sales teams become better equipped to service customers, respond to requests or challenges, and even predict customer buying behaviors. Understanding customer expectations and knowing how to manage them in advance is important not only for the timely delivery of existing products, but also for the promotion of new ones that customers may want or need downstream.
One such ability AI can offer a CRM is predictive lead scoring. Lead scoring is a way businesses and organizations identify and prioritize the highest-quality leads for their salespeople to connect with through a type of scoring system. As a business grows, this helps salespeople manage their time and pursue those leads that make the most sense.
Lead scoring with AI uses algorithms instead of people to predict which leads in a business’ database are qualified. Not all parameters are the same when predicting lead scores. AI easily can factor in information such as forms completed on your website, behavioral data, social media information, demographics, and even external information posted about your company.
With AI for predictive lead scoring, algorithms evaluate what information your customers have in common, as well as what information your leads that did not convert have in common. From there, the algorithm determines a formula that will organize leads for you automatically, so you easily can identify the most qualified ones. Imagine having to do this manually, and you can understand why AI is important for predictive lead scoring.
AI and Sales Forecasting
Along the same lines is the use of AI in sales forecasting. Sales forecasting is the process of estimating or looking ahead to sales downstream. Accurate sales forecasts can help companies make data-driven business decisions and predict performance both in the short and long term.
Sales forecasts can be based on industry comparisons, market trends, or even past sales data. With AI, companies can gain a better understanding of future revenue, improve resource allocation, better align teams with objectives, and calculate growth models.
If setting prediction parameters around your sales pipeline is difficult or unclear, or if sales forecasting is inaccurate, despite lots of legacy or current CRM data, you may need AI support in this regard.
AI and Natural Language Processing
Another powerful feature of an AI-enabled CRM is natural language processing (NLP). There are several ways people define NLP, but most tend to describe it as the ability of computers to understand and interpret human language the way it is written or spoken.
When a machine processes texts or spoken words from humans, they’re looking at data in 1s and 0s and not really hearing words. For AI to understand what you’re saying and turn those words into an action, NLP comes into play. Definitions aside, NLP can be used in several ways to enhance customer experience through a CRM.
For example, it can be used to determine what customers want from an email or text-based message. Customers or prospects often make similar requests through emails. A financial-based organization, for example, may receive daily messages from customers requesting new checks, or to open a new account, apply for a new credit card, or report a stolen card. Natural language processing can scan these messages and begin working on them before sales and customer support get involved.
What’s more, NLP then can determine which customer requests to prioritize. Reporting a stolen card is clearly more urgent than needing new checks. NLP can push customer and prospect requests that are urgent or time-sensitive to the front of the line, where sales and customer service can respond quickly.
When enabled through AI, NLP also can examine customer email interactions to get a better understanding of their experience, whether positive or negative. An organization that leverages insights in this way can remedy customer issues quickly, before they escalate.
Sales departments also can use AI to record voice meetings and phone calls, time-stamp specific notes, obtain transcripts, and even identify topics or words of specific meaning — like “budget,” “pricing” or “actions items” — or even target specific people. Sales teams then can return to exact moments in conversations after the call, glean specific insights, and combine them with existing CRM data to determine a best course of action.
Going deeper, AI can be used to analyze speaking patterns, word choices, or voice inflections to determine a caller’s emotions and offer resolution recommendations to sales reps, which could include telling users to slow speech pace, soften their tone, or even prompt supervisors to get involved when necessary.
One of the best ways for businesses to understand the needs of their customers is through tracking feedback, which can be collected through questionnaires, reviews, online comments and more.
A well-constructed survey can provide insightful and quantitative data, discover problems or challenges, and ultimately help a business gauge its progress or improvement over time. AI technology can not only streamline customer feedback programs and tactics, but also help companies eliminate unnecessary actions by evaluating communications that happen naturally every day.
At their core, CRMs are designed to store customer information and lots of it. AI easily can be applied to keeping customer records and information up to date, with little human help or data entry. These days, there is significantly more information than name, address, phone number and email that can be harvested and added to a customer’s profile, including social media channels, applications used, and even popular geolocation visits.
While AI can help sales teams dig through industry and social media data, it also can help companies properly allocate dollars to increase account-based marketing’s return on investment. Sales leaders can be handed high-value accounts or prospects that that meet very specific criteria, as well as search for others that are actively looking to buy. This can help marketers focus marketing and advertising funds toward prospects with the highest buying interest and prioritize engaged leads.
Who Needs AI?
Now that we’ve touch on a few ways AI can be leveraged in your business’ CRM system, the question is, do you really need it — or is it just another superfluous addition that won’t provide you with any real value? Not surprisingly, the answer depends on your business.
The common denominator, however, is this: The more data your business collects about customers and prospects, the greater the need for a CRM solution that can not only analyze all the data, but also provide useful insights and recommendations.
The move toward more powerful and more efficient CRM systems that reduce costs and save time is now possible thanks to AI. In today’s digital age, prompt, personalized and predictive services are essential to guaranteeing customer satisfaction and creating brand loyalty.
Businesses that utilize the full power of their CRM will find value in an integrated AI tool. On the other hand, organizations that struggle with their CRM, or with figuring out if they need one, likely will find AI confusing and unnecessary.
At the end of the day, CRM and AI are just tools from the sales and marketing toolbox. Neither replaces a thoughtful marketing strategy targeted at the right time, at the right audiences, and in the right context.
Conversely, a solid marketing strategy is only as good as the technology it sits on. Before leaping into the AI waters, master the fundamentals of your existing CRM. Once you’ve done that, unleashing the power of AI will help strengthen your sales and marketing teams and improve customer satisfaction.