The 8 HOTTEST CRM AI trends to put eyes on in 2018


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If you got wedged under a rock in 2017, it may be both a blessing and a curse that you missed the CRM AI media frenzy. AI showed up everywhere, rivaling electricity’s systemic emergence a century ago, allegedly injecting sage-like wisdom into everything from sales forecasting tools to email subject lines generators.

CRM AI trends

But buildup and hype aside, real progress was made in some impactful areas as unprecedented investments poured in. More resources supporting great minds pushed forward innovation in areas like image recognition, voice technologies, and natural language generation (NLG). And savvy brands that mindfully wired these into CRM applications boosted performance, in some cases realizing 400 percent ROI. Here are eight areas worth watching in 2018 that saw significant headway and are poised to advance further.

Data, data, data and speed, speed, speed
Like real estate’s mantra of location, location, location…. machine learning’s very foundation and success are predicated on choice training data and blazing processing speed.

But for data lovers, just as the internet giveth, during its unabashed wild-west data rush era, privacy laws spurred on by libertarian outcries soon may taketh it back. So, keep an eye on data privacy regulations, such as GDPR (which takes effect in the European Union in May 2018), as they could seriously impact future data availability.

Regulatory environments notwithstanding, with abundant data stockpiles and processing speeds continuing an inexorable march forward (vis-a-vis faster GPUs and cloud computing), expect more advances. For example, firms will latch onto progressive profiling and incremental data hygiene methods to refine first-party data, as emphasis shifts away from second and third-party data sources subject to stricter privacy regulations.

Capital One did just this in a routine email sent in late 2017, when they requested members update annual income data on file (previously obtained by appending from a third-party source), suggesting that if customers cooperated, higher lines of credit would be their bounty.

2018 will see more of this type of activity. Organizations will harvest and grind their big data crops, sifting off customer behavior insights aimed at deepening relationships and selling more products faster using less resources. Anticipate more investment in customer data platform, compiling, virtualization, and rationalization initiatives, with more computing horsepower and human capital helping the harvesting efforts in 2018.

Get your bionic ears & voice on
As humans, we’re obsessed with creating and perfecting tools that overcome our limitations, take our skills to new levels, and make our lives better. And last year marked the point that AI devices such as natural language processing, text analytics, and language generators stormed the commercial scene and provided CRMers and marketers with enhanced listening and speaking abilities.

Listening means understanding not just hearing. Enterprise CRM experts were graced with technology that can listen and understand millions of customer inputs simultaneously across a plethora of channels. Call scripts, reviews, complaints, social posts, and a host of other forms of feedback can be ingested, concept labeled, checked for sentiment, and gleaned for intent. Look for more applications and advances that propel the viability of using tech to listen and understand the voice of the customer at scale.

Although Siri, Alexa, Amelia, Cortana, and other AI assistants weren’t born in 2017, they arguably came of age, infiltrating our homes, and entering the workplace. If you didn’t catch it, Amazon announced Alexa for business at its re:Invent conference in November. Machine voices will continue to spread to business places like conference rooms, service channels, products, and kiosks. And companies (such as HSBC, Citi, and Barclays) found voice signatures another reliable biometric authentication tool to streamline digital transactions.

In 2018 AI may not replace you, but using it to handle routine tasks, listen to and converse with customers, and accept it as part of your marketing, service, and sales team will be essential to your survival, as you’re asked to up your productivity and customer experience enhancing game.

Voice recognition


Put AI eyes on customer data, journeys, and marketing content
Discovering, understanding, and learning from customer journeys requires mechanisms to observe and quickly answer question such as:

• Which customers are eligible for offers, got them, and responded
• Where do customers struggle, pause, or get stuck in their journeys
• What sequence of offers and channels lead to conversion (attribution)
• When do certain customers show up on the CRM radar; and when do some drop off and why

CRM specialists started using journey analytics to piece together the customer behavior puzzle, and the tech got better at going beyond business intelligence guesswork to prescriptive AI. More AI vendors bubbled up offering solutions that don’t just sum and sort data, but provide an analysis layer peppered with NLG narratives (such as Narrative Sciences and Arria). Others majored on providing better path-to-purchase journey visualizations, like Clickfox and Pointillist (although its arguable whether these are really AI tools).

And some focused efforts at bringing image recognition to real CRM AI use. Deep learning and image recognition applications went far beyond surfacing that labradoodles and fried chicken appear related. AI image processing proved its mettle for filtering and categorizing marketing and sales content, helping marketers better understand customers’ content needs and serve them appropriate and relevant content and offers. Brands began expediting and personalizing services using the ubiquitous smartphone and AI’s ability to pinpoint products and people in pictures and video. For instance, Aurasma launched an app that democratizes adding augmented reality to a consumer experience by simply triggering a video or animation overlaid on a smartphone screen based on recognizing a pre-defined image.

“Hey AI! Create me some emotionally compelling content”
CRM and marketing pros earn their pay by crafting compelling content using words and visuals to express value and elicit responses. They dance their evocative content lures in front of consumers knowing those customers will strike if needs are met and emotions satisfied. But up until just recently, most of these assets were home spun.

Yet last year, avant-garde marketers began applying AI to content generation, realizing that to compete in the new world (where content must be both mass produced and highly personalized), old tools must give way to new ones.

And firms like Persado began facilitating the march toward marketing’s creative nirvana, using NLG, emotional science, and machine learning to optimize (down to the preferences of an individual) the attractiveness of marketing offers by altering language, font, color, position, and other creative formatting. Results are not just encouraging, they’re somewhat staggering: click-through-rates (CTR) increased by 195 percent; conversion increased by 147 percent.

Natural language generation NLG


In one case using this technology, Amex Rewards generated 393,000 versions of engineered copy for its banner ads aimed at getting a customer to burn down their rewards points. The winner drove an 8.6% conversion rate, thumping the control’s 3.5% rate.

Self-driving CRM – Your AI digital agency
Practitioners continue to debate whether machine learning data prep, analytics, and marketing in general can be fully automated (particularly at the enterprise level), but nonetheless, the tools keep coming.

To this end, an interesting arrival on the scene was a vendor called, albeit clearly for down-market marketers. It’s literally 8 steps to setup and run a multi-channel campaign:

1. Enter name and dates for campaign
2. Select audience by city, interests (mix of music, pop culture, shopping, sports, etc..) or look-a-like targeting; age (typical bands); gender; language
3. Decide on display ad on desktop or mobile or both
4. Specify budget (e.g., $1000)
5. Upload display ad creative image
6. Add social media promotional ad (if desired)
7. Add URL for click through (analytics tracking automatically setup in Google Analytics)
8. Enter payment method (credit card or PayPal)

Simple and unsophisticated? Check. Will this kind of tech put further pressure on enterprise vendors to make their tools easier to use? Check.

Explainable and transparent analytics and AI
As machines crunch data, score customers, make predictions, and automate CRM and marketing, being able to explain to humans what’s going on and why is becoming more important.

Some models are very opaque, and simply can’t explain themselves. Given this, firms will need AI controls in place (such as offered by Pega) to prevent opaque models from being deployed in certain situations. Others are more transparent, easier to tease apart, and safer to unleash. Research and applications are stepping up in this area, so stay tuned, especially as more regulations emerge such as GDPR, that dictate data rights and demand algorithmic transparency.

Building one AI brain
Like opinions, everyone seemed to have an AI software brain to peddle in 2017 including:

• Einstein from SFDC
• Watson from IBM
• Sensei from Adobe
• DaVinci from SAP

What was less clear, however, was if each had one coherent well-integrated brain – or instead a multitude of disparate intelligence modules from the various acquisitions. In the case of SFDC, for example, between 2012 and 2016 they acquired 21 companies, of which at least nine had some form of CRM AI tech.

Stay tuned to AI developments from these and other leading CRM vendors, and pay close attention to whether they demonstrate real intelligence integration in the solutions they sell.

AI organizational dynamics – It’ll take neats and scruffs to tango
Accomplished scientists and artists have rarely been cut from the same cloth. In 2017, Walter Isaacson released his long-awaited masterpiece, the biography of Leonardo da Vinci, adding it to his corpus of history’s best examples of exceptions to this rule (Ben Franklin and Albert Einstein being other similar biographies he’s written).

So rather than wait for enough Da Vincis to come along, organizations would be wise to work toward making connections across AI and creative disciplines, which will be key to maximizing their capacity to innovate.

Along with attracting, merging, and retaining the right talent, brands must also acquire the right AI technology, but even more important is having a concerted AI strategy closely coupled with business objectives and CRM improvement goals. It’s imperative to work from well-defined use cases and clearly articulated outcome definitions backward to the technological and data solutions necessary to support them. Further, firms must use nimble organizational structures with small teams made up of neats and scruffs; IT and the business; re-aligning resources into small digital factory teams that are wed to agile methodologies and collaborative approaches.

On to 2018
In all, 2017 was a banner year for CRM AI, in terms of both hype and legitimate commercial progress. Keep track of these eight areas, and you’ll be following the most interesting and promising leading-edge AI technologies and trends that will prove paramount to success in improving and automating CRM and customer experience.

Vince Jeffs
Vince is a Senior Director for Product Strategy in Marketing & CX at Pegasystems. He has spent over 30 years as a product manager, consultant, and analyst in Marketing Technology. He works with enterprises to bring value to their customers by effectively using technology to improve customer experience. He has also been with IBM, Unica, SAS, and various Marketing agencies, and is a certified Professional Direct Marketer. Vince has spoken, blogged, and written on hundreds of Marketing technology topics. He is a proud alumnus of Georgetown University and the University of Maryland.


  1. Hi James, thanks for the comment. I wasn’t attempting to list them all. And I left out my company’s also (Pega Customer Decision Hub). But thanks for the info. Great to know.


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