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AI-as-a-Service in Martech: Focus on Virtual Assistants

Cognitive Automation, Neural Intelligence, Emotional AI, Conversation Assistants, and Proximity Guides — AI as a Technology Has Come a Long Way Since Its First Mention in a Sci-Fi Novel in the Last Century

I always felt that Issac Asimov and Sigmund Freud would have made a fabulous pair as a CTO and a CMO, running a tech company in 2018. Why? Science and creativity, with a touch of human emotion, can solve all the pain points that marketers face today.

Most marketing leaders would agree that AI will remain a buzzword for marketers in 2018. However, brands are expected to capitalize on the power of chatbots and virtual assistants to remain present throughout the customer journey to better understand consumers and amplify their purchase decisions. This is where companies providing AI-as-a-Service would gain maximum traction in the martech industry.

“The success of chatbots and AI is reliant on time and actionable data.” – Mahi de Silva, CEO,

A new report on martech hiring trends says that CMOs are most likely going to hire and pay higher salaries to executives with a strong background in Data and Analytics. While marketing leaders are divided on what trends would finally shape martech budgets in 2018, we believe that a large part of that budget is going to be reserved for the Big Tech powered by Data Science, AI, Machine Learning, and Analytics.

In Part Five of our Predictions 2018 Series, we bring cutting-edge insights on leveraging AI-as-a-Service from global representatives at Allocadia, Blis, Bospar,, BrightEdge, Cobiro, DiscoverOrg, Distil Networks, IRIS.TV, Marchex, Reveal Mobile and Webdam.

Maturity of Data Asset Management Platforms Would Reveal the True Power of AI and Analytics

Bob Hickey, GM of Webdam, spoke to us about the trends in Data Asset Management (DAM). Bob said that DAM would continue to converge with Marketing Resource Management and will become the platform of reference for the entire content lifecycle. He said, “Companies want and can expect powerful capabilities that aid in the content creation, reviews and approvals, brand management and asset management.”

He added, “DAM will get another boost as it supports external activities through integrations with social media tools, PIM systems, CMS, eCommerce platforms, CRM software and more.”

In all these, AI-powered DAM delivering relevant analytics would make the biggest disruption in the martech ecosystem.

“For 2018, I predict that the use of AI will continue to grow, accelerating content upload and organization, and increasing content effectiveness through predictive analytics.”

Bob said, “The increased reliance on DAM will also bring about more powerful analytics. As the central hub for creative content and collateral, DAM houses a wealth of data. Providers will focus on adding capabilities that turn this data into robust measures and reporting, providing essential insights to customers. Users will understand the impact of their assets, best performance, usage, etc. Artificial Intelligence continues to become an integral part of the analytics equation as it’s further integrated into DAM platforms. AI and analytics are also poised to accelerate the speed of asset ingestion, marketing execution, and performance tracking/ROI.”

Investments to Grow in Native Voice Experiences

Ryan MacInnis, Director of Marketing at Voysis, predicted that web and native voice experiences would go hand-in-hand in 2018. He said, “Marketers will be distracted by building consumer experiences on voice-enabled devices. When Amazon and Google own the platform, they decide what content is served to their users, and liquidate your brand even further — marketers should invest in native voice experiences, that complement effort on mobile.”

Ryan adds, “Marketers will have access to voice data (if they do #1) which will give them even deeper insights into consumer behavior.”

Highlighting the arithmetic relationship between brand messaging and distribution, Ryan said that marketers will need to understand that brand > distribution. Ryan said, “50% of Gen Z, the next generation shoppers, use voice to search daily. Given that brand loyalty is at such a premium, marketers will need to find ways to work voice into their brand strategy, incorporating it into their overall digital presence, as a way to differentiate themselves in the market, and continue to delight and inspire their consumers.”

AI-as-a-Service will Drive Digital Transformation in 2018 Big Data + AI = Personalized Experiences that Drive Performance

Kevin Bobowski, SVP of Marketing, BrightEdge, predicts, “With the rise of the experience economy, successful brands will crack the code on delivering a great customer experience and driving performance. For brands to reach the connected customer in more meaningful ways, big data and AI (finally!) play a critical role.”

Kevin added, “Using AI and specifically deep learning, brands will finally make use of their valuable data to tie together a personalized experience that drives performance. At BrightEdge, we’ve integrated deep learning into our platform, which makes it easy for marketers everywhere to use the power of AI in their daily marketing activities.”

“AI will begin to make its way into everyone’s lives in the form of chatbots for customer service and removing interfaces from the exchange of data for services in the case of products like Google Home, Nest, Alexa, SIRI.” – IRIS.TV, CEO, Field Garthwaite

Guy Weismantel, EVP of Marketing at Marchex, said, “AI will also contribute to substantial improvements in call analytics, providing data points that help marketers improve call center performance, identify high-intent callers by keywords, and retarget non-converting callers.”

AI in PR Tech: A Growing Phenomeno

According to Bospar Chief Content Officer, Tricia Heinrich, “As we Tech, PR, and marketing pros look at 2017, many trends and buzzwords come up – most notably artificial intelligence, big data, and digital transformation. My 2018 prediction is that we’ll see an AI, big data and digital transformation backlash by prospects, analysts and the press and greater selectivity about the vendors and stories they cover.”

Tricia added, “Claims around these buzzwords will receive greater scrutiny and potential debunking, meaning that ‘legit’ companies with demonstrated solutions will rightly continue to obtain media attention and market interest, while those which aren’t really delivering will struggle to attract relevant audiences.”

AI-as-a-Service will Largely Project Chatbots as Mainstream Marketing Icons

We are already seeing chatbot used by brands to engage customers via Facebook Messenger, Instagram and the like, and based on those results, we can expect to see more in the future.

CEO of Botworx’ai, Mahi de Silva, said, “The workhorse behind AI-assisted marketing will be chatbots, that will emerge as the key channel for customer engagement and far surpass email when it comes to targeting the millennial generation. This tactic of marketing has been dubbed conversational commerce, and it allows brands to use contextual data about their customers to interact with them the same way a salesperson would in a retail store; providing that interpersonal communication on a global scale.”

Mahi adds, “I would predict that 2018 will see chatbots become mainstream on Twitter, iMessage, Google Message, Snapchat, and all other key modes of communication. I expect this to lead to a shift in content strategy with marketers that once aimed to have “Likes” and “Followers” will now have “social messaging subscribers” and move the feed-based brand engagement to a message-based brand engagement that is personal to each one of their customers.”

Mahi further stated, “The success of chatbots and AI is reliant on time and actionable data. Machine learning, like human learning, can only improve with practice and experience. 2017 was a huge year for AI and chatbots in the marketing world, and many of these systems have gone through the learning curve with their bots, making them far more intuitive when it comes to engagement with human users. This is what makes 2018 so exciting, in that we will finally begin to see the fruits of this labor and a new age for AI and marketing.

Bots: The Good, the Bad and the Ugly

Elias Terman, VP Marketing at Distil Networks, feels that it’s time for marketers to realize that the technology that has the biggest impact on marketing is not some new cool app or the ground-breaking functionality from a vendor. It’s the effect of bots on their business!

Elias explained, “Bots, at their core, are pieces of software that crawl the web and perform automated tasks at a volume and speed beyond human capability, and they hit every website in the world.”

Elias expounded, “‘Good bots’ can deliver useful services to your website, such as virtual assistants (chatbots), search engine indexing and website performance monitoring. Marketers are also big consumers of bot-driven services that can help them improve search engine optimization (e.g. SEMRush and Moz), and ensure their pricing is competitive (e.g. and Upstream Commerce).”

AI-Driven Content Marketing and Advertising Platforms to be Adopted by SMBs and Agencies

Cobiro CEO, Bo Krogsgaard, feels that amongst US-based SMBs, 61% of them are not ready to use AI. The main reason is that they consider it overkill, expensive and difficult to deploy and perhaps most importantly, they do not have the expertise. For Cobiro and companies providing AI-as-a-Service have a huge opportunity.

Bo adds, “2018 would be about helping companies gain results from AI, without them knowing the details of AI. It is a little like a car that brakes automatically if people are texting or losing focus on driving the car. People are not interested in all the sensors and stuff that makes it brake, however, they are happy it reduces all these small accidents that can actually turn out to be fatal.”

The Growing Proximity Between Location Data and AI/ML Capabilities

According to Gil Larsen, VP of Americas at Blis, “In 2018, brands will place greater emphasis on location intelligence.”

Gil said, “Previously, brands focused mostly on proximity advertising but now we’re seeing advertisers turn to more sophisticated uses of location data to inform their campaign. By analyzing historical location data and detailed behavioral patterns, brands gain comprehensive insights into consumer preferences and habits which can be used for hyper-targeted campaigns.”

Location Data for Omnichannel Marketing Customization of Buyers’ Journey

Brian Handly, CEO, Reveal Mobile, predicts that modern marketers will continue to embrace use cases for location data beyond proximity-based push alerts and advertising. The location will be used to enhance more aspects of the shopping journey, including in-store augmented experiences, simplified mobile checkout, product reviews and tutorials, and in-store navigation.

Brian said, “Machine learning will be applied to location data audiences. Up to this point, audiences have been largely defined by devices that have been to a location. We’ll start to see predictive modeling used to find devices that are expected to visit a location in the future.”

Use of machine learning would also impact the way data management platforms fight fraud and data privacy issues. He said, “Fraud will creep into location data sets. As much as data buyers became aware of issues with overlapping datasets in 2017, they will become aware of the monetary impact of fraudulent data in 2018.”

The CEO of Reveal Mobile continued, “As much as marketers will love using location data, there will be a corresponding rise in questions and articles about who collects location data and how, how it is used, and ultimately kept secure. Because location data feels much more personal, it requires greater sensitivity, transparency, and security from any company working in the location industry.”

Convergence of Big Tech into Martech Stack with the Rise of AI-as-a-Service

Katie Bullard, Chief Growth Officer of DiscoverOrg, predicts that 2018 will be the year of MarTech convergence. “CMOs–and their entire teams–are overwhelmed with more than 5,000 tools that all do a little of the same thing, and trying to make sense of and utilize the technology has become wildly inefficient–both in terms of time and money. I firmly believe that in 2018, marketers will get smarter about rationalizing technology purchases, and in parallel, vendor categories will rapidly converge and consolidate.”

While we expect CMOs to tighten their martech budgets, there is a huge possibility that they would look to expand their vision in adding AI-powered capabilities into their existing marketing stack. AI-as-a-Service providers have a hay day to look forward this year!

Sam Melnick, VP of Allocadia agrees and states, “Marketing budgets are down for 2018, and so is spend on Marketing Technology according to research from Gartner. Marketers would now be held to a higher standard and while AI, predictive analytics, and other buzzwords (blockchain!?) get much of our attention — the reality is, most marketing organizations are simply not ready for these advanced technologies. Instead, those that were able to keep – and grow – their marketing budgets for 2018 have realized they need to take an honest look at their MarTech stack and get back to the foundational elements of data, technology, and process.”

With the maturity of marketing automation platforms and the marketing intelligence tools, the way each company monetizes AI would vary in 2018. While tech giants like Amazon, IBM, and Google (I would push for Tesla too!) would largely use their proprietary AI capabilities to solve business challenges internally, marketing technology vendors would rely on AI-as-a-Service to cull information from their data streams and build a more prescriptive/ recommendation models for marketing, sales, and advertising.

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Mobile devices provide the answer. By revealing where consumers go, mobile location data can tell brands which consumers spend their time browsing similar products at a competitor’s store. Let’s say Target wants to reach out to consumers who usually shop at Walmart. They can use location data to identify—then target—those who frequently visit the competitor yet still live near a Target store.

But brands need to be careful before jumping to conclusions about consumers. Real-time location data provides important insights, but they can be strengthened when paired with historical location data.

For example, just because someone visits a high-end boutique like Chanel, it doesn’t mean that person has the budget to shop there—they could just be browsing. How can an upscale fashion brand find out which of those Chanel visitors are actually potential shoppers? Here, historical location data can help. It can reveal, for instance, which of those visitors go to private airports a few times a month or regularly visit Giorgio Armani or Versace stores. Chances are, these consumers will be a better bet for the fashion brand seeking to acquire new customers.

Keep Them Interested

What’s the first thing you do when you wake up in the morning? For most of us, it’s look at our phones to turn off our alarms before checking the weather and scrolling through our Twitter feeds. And throughout the day, we continue to stare down into the faces of our mobile devices: checking the news on the train, sending an email between meetings, or watching videos from our living room sofas.

In order to engage consumers on the devices we use day in and day out, advertisers will need to serve ads that make sense for the consumer depending on where they are during the day. To do this, advertisers must first ask the question: What do consumers want to see on their mobile devices and when? Consumers spend a third of their time online watching videos, for instance, but they aren’t going to watch a 30-second video ad while walking down the street.

To boost engagement, brands can use knowledge about a consumer’s historical and real-time whereabouts to reach out at the time and place that will produce the greatest level of engagement. To effectively grab the attention of a consumer that’s out and about, a banner ad may work best. Later that evening, when the consumer is at home using a tablet or laptop, a longer video on a larger screen may work well.

Inspire Loyalty

How can brands make sure they retain the new and existing customers they’ve worked so hard to gain? They must first recognize and show appreciation for their most loyal customers.

Most advertisers identify loyal customers by looking at newsletter subscriptions and online purchase histories, but they may be missing other valuable customers who prefer to shop in stores. By identifying devices that frequently visit a brand’s store location, advertisers can make sure they are recognizing—and thanking—all their biggest fans. When an existing customer comes into a store a certain number of times, for example, advertisers can deliver a thank-you message—perhaps offering the loyal customer a generous coupon to redeem in-store.

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Today, consumers want—and expect—ads to speak directly to them. In fact, 74% of customers feel frustrated when their online experiences aren’t personalized.

The easiest way for retailers to personalize content is by harnessing their first-party data. If a customer purchases a dress online, the brand can use what they know about her (her fashion interests, browsing history and email address) to customize subsequent content. For example, the brand can serve an ad via email that suggests a pair of shoes to go along with the new dress.

With CRM data, the retailer can see what the woman bought online, but do they know what she’s purchased elsewhere? Or what she does when she’s not shopping? This is where location data comes in. Retailers that layer location-based insights on to other sources of data can get to know where and when consumers shop at brick and mortar stores. They can also identify other behavioral patterns, including which day of the week and time of day they like to go shopping—data can enables greater levels of personalization.

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Once retailer marketers have identified their ideal audiences on mobile, they shouldn’t see phones as the only means of communication. Consumers own an average of 3.6 connected devices, so retailers should communicate with consumers across the devices they use, including tablets, laptops, desktops and addressable TV.

However, if a retailer sees a user reading political news on the tablet all day but watching cartoons in the evening, it might not be the same same person. With families and partners sharing devices at home, marketers need to make sure they are constructing nuanced consumer profiles across devices in order to reach out to individuals, not just devices.

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But how, exactly, do they measure these improvements? Find out next week when we assess the best metrics for retailers.

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