How are AI and data-driven campaigns changing sales and marketing?

How are AI and data-driven campaigns changing sales and marketing? image

Think of sales and marketing campaigns in a traditional sense and you may well dream up the heady days of billboard advertising or the golden age of television advertising. In short, these days are gone.

In a modern sales and marketing environment, rather than the art of advertising, there is now a science to marketing and as a result, sales. This change in the way sales and marketing teams are operating has also given rise to a more considered, results-driven approach.

Rather than approaching a marketing campaign or sales drive with a vague goal in mind, these days you are more likely to kick off a campaign with figures in mind both in terms of previous proof and predictable results. This trend is by no means new, but the advent of a more resilient and functional level of artificial intelligence (AI) has meant data is now more useful than ever before.


Profiling and evolving data

The hallmarks of a solid marketing campaign now involve data and building up an image of the end-user. The ways in which a typical customer profile is created has however changed from simply positing an A, B and C type.

Sales reps can spend hours trawling through LinkedIn and clicking through company websites. Through creating buyer personas, AI can speed up this process, making lead generation faster and easier. A buyer persona is a semi-fictional representation of your ideal customer, based on real data. AI can take the data, analyse it at speed, and continually update the persona in real-time. This makes sure your buyer personas stay relevant over time.

Now, multiple levels of detail can be drilled down into and more specific, dynamic profiles can be set out. The way data is managed, updated, and in effect, cleansed also means businesses wanting to ensure they are pitching, engaging with, and marketing to the right individuals has more chance of reaching the right people than ever before. Dynamic data systems, which can be updated in real-time and often automated, are making the difference between leads remaining prospects or becoming valued clients.


Improving internal teams

As well as prospecting and nurturing client relationships through AI, B2B sales managers can use the same kind of technology to supervise their own internal team’s performance. A recent study by found that six out of ten respondents (61%) saw the value of adopting AI to streamline day-to-day processes, of which this is just one.

This kind of streamlining can be done by assessing revenue pipeline, seeing which salespeople are likely to hit certain quotas, getting a snapshot of which deals stand a good chance of being closed – all are easy with AI.

The value for managers is in being able to identify high-performing salespeople and accounts that are likely to be successful, meaning that they can refocus energy and resources to those parts of their business. This not only improves sales processes and pipeline management but also lends beneficial processes to HR departments and those monitoring team performance and allows for adjustments to be made to ensure a smoother way of working.


Freeing up time

AI is already having a major impact for sales and marketing teams, especially when it comes to lead generation, but as the technology progresses, there will be even more advantages to the reach it can make in the future.

The cumulative effect of applying AI and big data solutions is in freeing up time for human workers. While machines take over the mundane, repetitive, and analytical tasks that consume so much of our time, we are free to think more creatively and work more effectively.

A good example for B2B companies is the traditional sales rep. If AI can manage the 22% of a day spent searching for prospects or performing administrative task, then that’s a sizable chunk of his time that he can now be used to engage with clients and close more deals.


Advantages of AI in aftercare

It’s not just the sales and marketing process that is set to benefit from some degree of AI or data treatment, after all, a sale does not just end once a customer is on board as a client or has purchased a product.

This is one area where a lot of businesses are already using AI to improve their processes. The more common use of chatbots is enabling 24/7 customer support, talking with and guiding customers at all times of the day. AI can also gather data from customer interactions and provide valuable insight and analytics.

By providing a smoother and more convenient customer service experience, AI will further help to heighten customer happiness. This will inevitably keep retention rates steady and gives marketing teams plenty of material to work with through satisfied customer testimonials and referrals.

The future, therefore, isn’t one of robots taking over and replacing all human interaction and workplace responsibilities, rather the considered assistance that comes with properly-managed data and AI systems. There is a future out there to grab immediately, it’s knowing how it is applied that will place the early adopters front and centre.

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AI’s Role in Driving the Sales Experience

AI sales process

Much has been made of AI’s role in serving customers, and AI-supported smart devices have invaded homes everywhere — Amazon’s Alexa was even used to order millions more Alexas as Christmas presents in 2017. Artificial intelligence is embedding itself in our technology-obsessed culture, but not every industry has taken advantage of AI’s utility.

Adam Honig and his co-founders at Spiro saw an opening to use AI to drive the sales experience. Businesses utilize CRMs to compile and track the data needed to support ongoing sales efforts and pinpoint new sales opportunities. But Honig, the CEO of Spiro, says that many companies aren’t getting the data they need from these platforms — they aren’t used correctly, fully, or consistently, meaning the information these sales teams are working from is skewed.

Spiro is an AI-driven CRM, complete with a conversational email interface, or an email bot, that utilizes existing data — from salespeople’s calendars, emails, and more — to lay out a schedule or to-do list for a salesperson and anticipate next moves. The AI function can process existing information more quickly than humans poring over spreadsheets can, empowering the CRM to predict how many follow-ups it may take — and what format will be most effective — to close a deal.

But that’s not where Spiro sees AI’s intersection with the sales experience ending.

How a People-Driven Industry Benefits From AI

It’s well-known that AI can process data better than humans can — a Massachusetts Institute of Technology startup’s software developed stronger predictive models than the majority of its human competitors did, and some predict that AI will be better than us at everything by 2060. But even then, there are limits: Eleni Vasilaki of the University of Sheffield says there’s “little evidence that AI with human-like versatility will appear any time soon.”

That’s what confounds many: How could an industry fueled by personal relationships, charisma, and camaraderie be driven by AI? Sales is surely a people-driven arena, but it’s already focused on tracking metrics and moving the needle by predicting human behavior. Honig and his co-founders realized, through their CRM work with more than 3,000 companies, that the problem lies in the data being gathered.

“To say that salespeople hate CRM is an understatement; most consider it a soul-sucking beast of burden that doesn’t add any value to their sales life,” Honig says. “We knew that salespeople desperately needed a CRM that would help them make more money, not give them more work. When I saw the movie ‘Her,’ I realized that the new AI technologies that were emerging would be perfect to automate non-sales tasks so they could focus on selling.”

Is This the End of Sales as We Know It?

Beyond increasing productivity and efficiency, automation can relieve salespeople from manual tasks, freeing them up for more high-level strategic efforts. Though many predict that AI will lead to mass unemployment as human beings are relieved of their duties, AI is designed to elevate the skill sets needed in each industry so complex, nuanced problems with big implications are solved by humans who will have to absorb those outcomes.

That’s why Honig believes AI will augment, not replace, salespeople. “In some ways, AI is already replacing salespeople at a fast pace,” he says. “’s AI algorithms make specific purchase recommendations and provide a high level of service that’s hard for retail salespeople to match.”

What that means is that to compete, salespeople selling to businesses have to be prepared to embrace solutions that make them more effective with customers. “In practice, this means using AI solutions to do things that technology can do better, like entering data, and let them focus on the things that people do better, like building rapport and really understanding the needs of a customer,” Honig explains.

The Productive Path Forward

The biggest benefit AI may offer to the sales process is its data-gathering capabilities. Whereas some salespeople operate from instinct or their “gut feeling” about a customer and his needs, sales is often now held to the same standard and expectation of ROI as most marketers and advertisers. Without numbers, it’s hard to maintain a budget, commission, or even a permanent position.

Despite this need for hard data, many sales departments track information haphazardly, failing to record final contract numbers in a database or neglecting to indicate how many touchpoints a lead went through before finding his way to the bottom of the sales funnel. That lack of information may not impact that specific sales process, but it can alter an entire team’s goals and predictions. AI-driven platforms like Spiro can grab the data where it’s buried and build their own reports, adding a layer of analysis and interpretation for human reviewers. Honig says Spiro’s reports have been shown to contain eight times more data than regular CRM reports, underscoring the power of AI.

The other side of AI’s productivity can be seen in its ability to look at an overview of a person’s behavior, add context, and predict future actions. “Imagine if your CRM could advise you who you should call and follow up with to drive all your leads and deals forward,” Honig says. “That’s what we do. Spiro uses a machine learning algorithm that was trained by more than 15,000 salespeople to identify the best times for follow-up, the best email templates to be used, and the best contacts to focus on.”

Thanks to these insights, Spiro’s customers have indicated they reach up to 47 percent more prospects each week. A big factor in reaching more customers is having the AI predict which prospects won’t close so salespeople can focus on others. Human hope makes it hard for sales professionals to shut down a potential source of income when they can’t see where the road ends.

“Artificial intelligence will do more and more for salespeople,” Honig says. “Beyond advising them who to call and follow up with, it will automatically identify similar prospects and suggest that salespeople call them. It will listen in on sales calls and provide real-time feedback to help make the pitch even better. It will learn from emails, calendar appointments, and phone calls to craft specific proposals based on what’s already happened.”

In other words, Honig predicts AI will become salespeople’s constant companion, designed to help them make more money. Sales may be a people-driven industry, but AI is on a path to ensure it values data as much as instincts.


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Five Ways To Use AI In Marketing Today

laptop with marketing displayed

Recently I was asked, “As an agency, how are you using AI within your marketing?” And honestly, the question gave me pause. I know we are using AI, but could not answer exactly how. Since it was (and is) a really valid question, I wanted to have a really good answer the next time someone asks.

Artificial intelligence (AI) boils down to a relatively simple concept: using machines to process data and automate repetitive tasks. And in my experience, AI also helps with seamless integrations that have been overlooked and taken for granted.

While AI, by definition, seems quite simple, the execution and process are not. Developing a program that can mimic the human brain, solve problems and apply reasoning is actually quite complex. We are lucky enough today that there are multiple box-like solutions that we can apply to our challenges without the demand to design and develop them.

Today, I’d like to open the discussion to five internal applications for AI that you may not have integrated into your practice yet. Based on our own agency’s experience with them, I believe that each of these, while simple to integrate, also streamlines workflow, reduces errors, cuts costs and delivers better insights.

1. Sales Predictions: Our sales team relies heavily on a CRM system to house information on clients, prospects and sales history. To date, much of this has been a library of information with search functionality. However, we are seeing systems such as Salesforce, Active Campaign and many more, beginning to incorporate predictive analytics (AI) into their services. We can now search our database for most engaged leads and prospects most likely to close, along with other key indicators. This seemingly logical information has allowed our team to focus their time and energy on yielding improvements in the close-rate percentages as well as shortening the time-to-close ratio.

2. Ad Bids: Google is leading the way in AI development, testing and integration (alongside Facebook, Amazon, Microsoft and Apple). If you are executing a paid ad campaign with Google’s search pages, you are likely using its artificial intelligence technology. Called Smart Bidding, the platform will test, monitor and adjust your Google Ads bid strategy with the intent of improving the quality and return on investment (ROI) of your ad campaign. In our experience, this is still new and needs consistent human oversight (it does not always work the way it should). However, as machine learning goes, we know it will gain intelligence and improve on the structure quickly.

3. Dynamic Ads: Use predictive analytics to serve the most relevant online ad to your prospective customers, and your ad buys will become exponentially more successful. For us, this means providing Google a list of landing pages we would like to use in an ad campaign. The program will then scan the pages and identify critical phrases and keywords for each page. Those are then injected into the paid search marketing campaign when an individual uses a search for a related product or service. Often, when dynamic ads are incorporated into a campaign, we realize a three-to-four-point increase in ad engagement.

4. Improved Internal Processes (And Fewer Errors): This is where the automated processes portion of AI has impacted our firm. We have automated our proposal tracking, follow-up and reporting processes between our software used to generate proposals and our CRM software. Additionally, we have implemented email marketing automation within our business development processes to send and personalize emails delivered, depending on the interactions by the recipient and the content they view within our website. We have also been successful in reducing staff time in campaign reporting, and have virtually eliminated errors in our client reports. Through linking the various ad platforms we use monthly (e.g., Google, social platforms, programmatic platforms and others), campaign data is shared directly with our reporting dashboard, providing real-time access to the data for our team and our clients. Combined, these have made our firm more responsive to our clients (building loyalty).

5. Chatbots: Chatbots allow brands to have conversations and answer inquiries, even when the office is closed. Our use of this technology is fairly limited at this time, but really, the opportunities are endless. Recently, I had a client testing this technology at live events to share updates and answer questions from attendees (e.g., Where is the closest bathroom?). Facebook Messenger has been testing and improving chatbots through its platform for a few years now and have gotten pretty good at carrying on a conversation without the challenges of 24/7 staffing.

I could keep going — there are many more potential applications for incorporating AI into your organization. Have you started testing any of these uses? What else have you tried that have been successful for your business?

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