Artificial Intelligence Is All The Rage; How Should You Use It To Drive Results?
So much to do, so little time. Marketing has never been more complicated.
With so many tactics, so many software tools to consider, so many different strategies and so much data to analyze, how can anyone make heads or tails from all of this stuff?
Now introduce the idea of artificial intelligence (AI), which is all the rage. Almost every software tool among the over 10,000 MarTech and sales tech solutions have some element of AI included in their stories.
But how many are really helpful, and how do you assess these AI tools to drive results?
Remember, the goal is to improve performance, drive more leads, get better leads for your sales team and then empower sales with tools to help them close a higher number of sales opportunities in less time. When this comes together, you’ll be the marketing superstar you aspire to be.
Here’s how to be proactive when looking to add artificial intelligence to your marketing and sales efforts.
What Is Artificial Intelligence (AI)?
If you’re interested in the history of AI, check out this great article from Built In that takes you from 1943 to today. Here’s an excerpt from the article:
Less than a decade after breaking the Nazi encryption machine Enigma and helping the Allied Forces win World War II, mathematician Alan Turing changed history a second time with a simple question: “Can machines think?”
Turing’s paper “Computing Machinery and Intelligence” (1950) established the fundamental goal and vision of artificial intelligence. At its core, AI is the branch of computer science that aims to answer Turing’s question in the affirmative. It is the endeavor to replicate or simulate human intelligence in machines.
While addressing a crowd at the Japan AI Experience in 2017, DataRobot CEO Jeremy Achin began his speech by offering the following definition of how AI is used today:
“AI is a computer system able to perform tasks that ordinarily require human intelligence... Many of these artificial intelligence systems are powered by machine learning, some of them are powered by deep learning and some of them are powered by very boring things like rules.”
If you’ll allow me to summarize: AI helps us use machines (software) to do what humans do somewhat inconsistently and do it faster and more consistently. AI also has the ability to learn just like humans and improve what it does so it runs faster and more consistently than some humans.
AI Is Already Everywhere
It helps Netflix recommend shows and movies based on your viewing habits. It helps Amazon recommend products to buy based on your purchase behavior. It controls the braking systems in your car. It’s the intelligence behind Siri and Alexa. But these are still fairly simple tasks.
When it comes to sales and marketing, AI is still early, but it’s here too:
- B2B companies that have leveraged AI in sales realized call-time reductions of up to 70% and a 50% increase in leads and appointments. (McKinsey & Company)
- A recent study found that by leveraging artificial intelligence and machine learning in combination with a human touch, a large toy retailer was able to reduce shopping cart abandonment by 30%.
- According to Tractica, ample scope exists for marketers to leverage voice assistants, AI and Robotic Process Automation (RPA) to drive growth.
- 61% of marketers say artificial intelligence is the most important aspect of their data strategy. (Venture Harbour)
- 87% of current AI adopters said they were using or considering using AI for sales forecasting and for improving email marketing. (Forbes)
- When AI is present, 49% of consumers are willing to shop more frequently, while 34% will spend more money. (AI Trends)
- Companies using AI for sales were able to increase their leads by more than 50%, reduce call time by 60-70% percent and realize cost reductions of 40-60%. (Harvard Business Review)
- By 2020, 30% percent of companies worldwide will be using AI in at least one of their sales processes. (Venture Harbour)
Some of your favorite marketing and sales tools already have AI built into them, including HubSpot’s marketing and CRM tools, Salesforce, Drift, Conversica, SalesLoft and more.
But let’s look at AI from a more practical and results-driven perspective. In other words, how can we use AI today to drive results?
AI Is Still Very Tactical
Revenue generation has always been very siloed. It started with the notorious feud between the Hatfields and the McCoys (marketing and sales). For hundreds of years, these two families fought epic battles. Marketing generates bad leads, and sales never follows up on the leads marketing generates.
Within those major family feuds, marketing specifically was very siloed. You had the website team (which in some cases wasn’t even in marketing with corporate communications) handling the company website. But you also had PR teams, email teams, paid media teams, the SEO team and the events team.
I know, because this is how my marketing team was organized when I ran marketing for a software company almost 20 years ago. Believe it or not, very little has changed, so it’s not surprising to see the AI marketing software tools also aligned tactically.
Import.io: Import.io allows you to import data from any web page, even if the data you’re after is hidden behind login forms or other elements. You can then compile this data into spreadsheets, visualizations or machine learning algorithms. (Data management)
X.ai: A perfect example of how simple and effective artificial intelligence can be – a refreshing break from many platforms that try to do too much. With X you’re simply looking at an AI scheduler that genuinely makes arranging meetings and other appointments effortless. (Meeting scheduling)
Grammarly: Another example of simple but effective AI – this time in the form of an intelligent proofreading tool. It’s not going to catch all of your writing errors, but it’s an impressive piece of software, and its integration with apps and browsers is incredible. It will flag up your typos as you write emails and blog posts in the browser and compile reports of your most common mistakes, so you naturally become a better writer over time. (Writing better)
Uberflip: An advanced content personalization platform that helps you create unique experiences for each customer. Content personalization remains one of the biggest challenges for brands, and Uberflip makes it easier to execute at scale for enterprise brands with a large, diverse audience to work with. (Content personalization)
Acrolinx: Before you can personalize content, you need to be able to create it, and Acrolinx helps you create highly effective content at scale. Acrolinx claims to be the only software platform that can “read” your content, thanks to its advanced artificial intelligence engine that assesses your content, grades it and guides you to creating better content. (Content creation)
If you want to see the other 16 tools Venture Harbour is listing, you can click here to see the full list, but you can also see that these five are very tactical and very narrow in their application.
I’m not being critical; it’s smart for software companies to pick a lane and stick with it, but this does mean that expecting AI to have a big impact across all of your tactics might be an overly aggressive goal today.
The Marketing Artificial Intelligence Institute looks at the AI ecosystem slightly differently. They identify planning, production, personalization, promotion and performance lanes by which to look at AI tools for marketers. You can see their view of the AI world below.
While I understand where both the tactical and the application perspective came from, I can’t help but wonder where the tools are that review overall program performance across all of your channels and across the entire revenue cycle (marketing, sales and customer service). That’s when AI will start making significant inroads in helping people drive more revenue.
AI Software Alone Won’t Drive Results – Operationalizing It Is The Key
Back in the early 90s, software was sold at the enterprise level, required millions in licensing and implementation fees, and only had a 30% successful implementation rate. Today, SaaS (software as a service) has solved a ton of those challenges except for one: adoption and retention.
Today, it’s easy to try new software. You sign up, turn it on and start using it. If you like it, you keep paying, and if you don’t, you cancel. This presents some new challenges for the SaaS companies, but from your perspective, you want software that drives results, not software that gets turned on and canceled four to five times a year.
The secret here is what I call operationalization. The web defines operationalization as the process of strictly defining variables into measurable factors. The process defines fuzzy concepts and allows them to be measured, empirically and quantitatively.
To me, this means removing all of the uncertainty associated with new software and wrapping processes and methodologies around the new software.
No matter what AI tools you buy, the questions you have to ask first are the following:
- “What are we going to do with the software?
- “How are we going to use it every day?”
- “How is everyone going to know what to do?”
- “What are our expectations? What improvement in metrics are we looking for from using the new software?”
Here’s an example of how we recommend companies use MAXG to drive results quickly. This is an excerpt from a playbook for purchasing MAXG, an AI-powered insight and recommendation engine for marketing teams.
Step 1 – Hook up your HubSpot account or your Google Analytics account to MAXG. This takes seconds.
Step 2 – Once MAXG is set up, you’ll instantly see a dashboard for your company and a list of insights, recommendations and performance benchmarks.
Step 3 – Since MAXG provides benchmark performance data, we recommend you look at how your program is performing when compared to other companies in your industry. You might be outperforming your industry peers and not even know it.
Step 4 – When you check your MAXG dashboard, the insights and recommendations are prioritized based on what’s going to have the biggest impact for the least amount of effort. You should consider using this prioritization methodology to assign work out to others in your company, if that’s an option. If that’s not an option and you’re a one-man or one-woman marketing department, just start at the top of the list and work your way down. This ensures you’re always working on the most important recommendation.
Step 5 – In the software you can assign recommendations to other team members in your company. By doing so, they’ll be alerted, and they can see the insight and recommendation assigned to them directly in MAXG. You can have as many people in the product as you want. Pricing is based on portals and websites under management, not people on the platform.
Step 6 – If you’re planning work in sprints, either weekly, bi-weekly or monthly, you’re going to want to use the recommendations from MAXG to plan your sprints. In some cases, you might be able to make very lightweight adjustments immediately, but generally stack up the recommendations and plan to work them into your next sprint.
Before you lock in the work planned, checking in with MAXG is a great way to ensure that you’re doing the right work, in the right order. This is going to immediately improve the program results, the efficiency of your marketing and the satisfaction of executives at your company.
Step 7 – MAXG has a slick new Chrome extension (illustrated in the picture above). This allows you to simply visit your website and (as long as you use the Chrome browser) see what adjustments should be considered. As you move through your site, you’ll see recommendations on pages, pillar pages, blog pages, landing pages, etc.
If you are working on site optimization, this is a great way to know where to start, and this is a great way to optimize site performance quickly.
If you are working on specific campaigns and you have campaign-specific pages on the site, this is a great way to optimize campaign performance quickly.
Step 8 – Because there are always areas for improvement, you should consider checking MAXG as frequently as you’re planning work. Our team checks MAXG weekly, but we check monthly to start planning our sprints and then right before we do backlog grooming and sprint planning.
If you expect your team to simply start using your newly purchased AI software without any direction, expectations or guidance, you’re setting yourself up for a situation where you’ll probably be canceling your subscription in a few months because very few people used it and you saw very little value.
This is going to be an operations failure, not a failure of the software.
An AI Strategy Is Needed
At Square 2, we have a strategy before tactics approach to everything we do, and when it comes to adding AI software to your marketing or sales tech stack, the approach remains key.
What are you trying to accomplish? How is this new software going to help you execute your strategy, tactics and analytics to ultimately drive more leads, better leads, more new customers and revenue goal attainment?
Specifically, what are you trying to accomplish? Do you need help building your website? Do you need help personalizing your content? Do you need help creating content? Do you need help managing your paid ad campaigns? Do you need help posting on social sites? Do you need to improve your email marketing performance? Do you need help with marketing automation like lead scoring, or do you need help with sales execution and follow-up?
It’s unlikely you’ll be successful researching, selecting, installing, operationalizing and gaining traction in all of these areas at one time. So pinpoint the greatest pain or opportunity, and then use that overarching strategy to give your AI software a focus, a mission and a purpose.
You might need help in all of those areas, but start by prioritizing and working on issue number one. Once that’s solved and you’re seeing return on your investment and goal attainment, you’re ready to move on to prioritized issue number two.
With so many areas of marketing, sales and revenue generation in general that need help, it’s likely you’ll always have areas that need attention.
AI Applications Ready For Prime Time
With all of these AI tools available for marketers today, how do you know which applications are ready for prime time?
I’m not talking about HubSpot, Drift, Salesforce, Marketo and the other mainstream platform products that have been out on the market and have extensive install bases. This section is to introduce you to some of the lesser-known and more AI-specific solutions that might be perfect for your tech stack.
To make this a little easier, the applications are broken into four key areas:
Personalization, the first of our four areas, allows you to more easily create personalized content and nurture experiences based on intelligence from user behavior.
Automation, the second of our four areas, allows you to take mundane tasks like posting to social or following up on leads and have the application automatically execute these tasks based on user signals and your nurture strategy.
Production, the third of our four areas, allows you to create content and educational materials in a faster, easier and less expensive way. Considering how important content is to earning the attention of your targeted prospects, creating it based on intelligence and doing it quickly can drive big-time program performance.
Insights, the final of our four areas, allows you to see what might ordinarily be buried in the mound of data facing marketers and sales operations people today. Dashboard after dashboard, chart after chart and graph after graph will only tell you so much. You don’t need dashboards; you need insights that shape your ongoing optimization and iteration to drive better performance.
The best is in the eye of the beholder. What works well for my company might not work as well for yours, so I’m not giving you a list of the best AI tools for personalization.
Instead, I’m introducing you to ways to think about improving personalization to drive a better customer experience, and then showing you a handful of tools that might help.
Cookie-cutter customer experiences just won’t cut it. And online personalization, once seen as a competitive differentiator, is now a strategic imperative.
Consider this: Nine out of 10 marketers say their customers expect individualized experiences. And according to Gartner, organizations that have fully invested in online personalization will outsell those that haven’t by more than 30%.
Most importantly (in all of these areas, but especially in the area of personalization), try not to boil the ocean. In other words, start slowly.
Applying personalization across all relevant channels – so customers are recognized and can pick up where they left off – should be the goal.
To do so, companies need to be able to:
- Track an individual’s behavior across different channels
- Merge that information with pertinent customer data from other systems
- Automatically interpret the data to determine affinities and intent
- House everything in a central place – creating a single, unified profile for each person
- Act on all of the data in real time
The most important element – and an essential part of all five steps – is, of course, data. Your personalization strategy is only as effective as the data informing it. Even the most advanced algorithms can’t work their magic if they have incorrect, inadequate or outdated data.
But I do not recommend that you wait to start personalizing until you have cleaned up all of your enterprise data. If you do, you will be waiting a very long time.
Start with your digital channels. It’s easy to leverage a next-generation personalization platform to start bringing in deep, contextual, real-time and accurate behavioral data from your sites, apps and email.
You can use this data in your personalization platform to create terrific results. Then leverage this success to start bringing in other enterprise data sources one by one, cleaning them as you go.
Some of the best personalization tools that use AI include:
- HubSpot, which can help you deliver personalized content options based on previous content selection.
- Drift, which provides a highly personalized website experience by putting visitors and live people together quickly via chat.
- BrightEdge, a leader in SEO and content performance marketing by lending search intent data and content creation to improve overall engagement.
- Skyword, which makes it easy to produce, optimize and promote content at scale to drive better, more meaningful and longer-lasting prospect relationships.
- CONCURED, which shows marketers exactly which topics drive engagement and what to write about next.
- CliClap, an AI-powered content marketing solution that predicts on-site conversions and allows users to personalize the content part of your buyer journey.
Like all software, taking mundane tasks and applying AI to make those easier for us to execute is a fantastic application for this new machine learning. Most marketing automation platforms promise complete or at least semi-automation capabilities, such as automation with regard to automated email, lead scoring, instant CRM data synchronization, lead nurturing, publishing cross platform and more.
In a Gartner study, they noted that by 2020, 85% of customer interactions will be handled without a human.
Specifically in the area of automation, which by design should make marketing, sales and customer service teams more efficient, Accenture found that current AI technology can boost business productivity by up to 40%.
Almost all of the CRM solutions have automation capabilities, and all of the marketing automation platforms do too, so to list all of those platform options seems a bit unnecessary. However, other tools provide additional automation capabilities for both sales and marketing that can drive significant program performance.
Some of the automation AI tools include the following:
- Conversica helps companies find and secure customers more quickly and efficiently by automatically contacting, engaging and following up with leads via natural multi-channel, two-way conversations.
- Seventh Sense automates the delivery of email based on user behavior, which drives delivery timing and frequency to improve open and click-through rates.
- Exceed.ai automatically contacts, engages, follows up and books qualified meetings. The automated two-way email and chat conversations work alongside reps to free up more time so they can focus on closing deals.
- PersistIQ helps you send better, more effective emails — emails that are personalized and error-free.
Creating stuff in marketing today is a huge challenge. Yes, quality is important, but quantity is too. You need video, e-books, whitepapers, website pillar pages, blog articles, infographics and social posts. Plus, everything you create has to be engaging, SEO optimized and as creative as possible.
Today, producing content is dependent on your team of designers, writers and editors. Even if you’re using an agency to help with content creation, you’re reliant on their team. The promise of AI-generated content has always been at the top of the AI wish list for marketers.
Some of the top production tools that use AI include the following:
- Atomic Reach is an AI platform that delivers deep insights on critical data points that influence and affect the performance of text-based content.
- Persado’s marketing language cloud delivers AI-generated language that resonates better with your audience.
- Scoop.it automates the content marketing process and provides insights on how to generate better results from your content.
- Automated Insights’ Wordsmith is a natural language generation platform that enables you to produce human-sounding narratives from data.
Insights (Skipping The Dashboard)
A CEO once told me early in my career that you want to create the business that will one day put you out of business. Today, marketing agencies help clients know what to do, how to do it and why they’re doing it. They gain insights from the data and use those insights to drive recommendations that improve program performance.
The challenge is that these insight only come from years of practical experience. You can’t read a blog, watch a video or attend a conference to learn what the data is telling you. You can’t learn how to structure the data to uncover those insights. You need to have the 10,000 hours of experience that help you know what to look at, what the data is telling you and what to do about it.
This is an excellent opportunity for AI to step in and help. Very few AI software tools today are looking holistically across your entire revenue generation efforts to provide you insights and recommendations.
Many AI tools look at specific tactical performance like content, email, lead scoring and lead nurturing, but only a handful look across your entire effort.
Here are some of the more innovative insight and recommendation tools using AI to give you what you need to improve performance quickly:
- MAXG is an AI-powered insight and recommendation engine that prioritizes recommendations based on insights uncovered from your HubSpot data. It looks at landing pages, CTA buttons, emails, blogs and your data. Each month, new areas are added to drive even more insights. The tool also benchmarks your current performance against other companies like yours. A Chrome plug-in makes using MAXG as easy as looking at your website.
- Equals 3’s Lucy reads and learns all of an organization’s accumulated knowledge across all of the different places the information lives. She takes written reports, PPTs, PDFs, videos, audios, graphs and datasets, and learns them like an expert. Ask Lucy for what insights you’re looking for, and she delivers the specific answer unit within the relevant assets.
- PaveAI provides insights from Google Analytics, with a focus on social ad programs and e-commerce conversion data.
If you evaluate today’s AI tools and all future AI tools in a similar way, you can be sure your process for selection is consistent and aligned with your company’s goals, which should be to drive additional revenue growth from your investment in marketing, sales and customer service.
We’re still in the early days of the AI revolution, and marketing is primarily driving the application of AI tools to drive revenue. However, now is the perfect time to start experimenting with AI tools at your company.
One of the nice changes to the software industry is that you don’t have to purchase expensive software anymore. Today’s SaaS-based model means you can trial products, use them for a few months to test them and if they don’t work, cancel the subscription with little or no risk to your company.
Yes, this requires an investment of time, and yes, you need to run the test long enough to make a thorough and comprehensive evaluation of the software, the benefits and the results. But even if you deem the test a failure, consider that important learning and move on to your next test.
If you deployed this approach, you could test roughly eight to 10 new tools a year and stick with only those that produced big results, had a relatively strong return on investment and were easy to use.
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