Artificial Intelligence Potentials in B2B Marketing – D&B

ai-dnb
AI Marketing

By Leslie Hancock
Founder & CEO
CreativeCafeHQ.com

I did an amusing and highly informal survey, asking various people in my life what they think about when I mention “artificial intelligence” (AI). Not surprisingly, most think of human-like robots or omniscient, self-aware computer systems as portrayed in The Terminator, Ex Machina or Person of Interest. There’s the unavoidable association with a dystopian future in which the machines wake up and decide humans are a blight that must be eradicated. Even luminaries like Stephen Hawking and Elon Musk have warned us of the potential dangers of AI. But the general public still seems to think of AI technology as something to worry about in the distant future, not something that’s already a factor in almost every industry and aspect of our everyday lives.

The truth is that AI is already here, and it’s pervasive. Though most AI tech is nowhere near passing the Turing Test and taking over the world, it’s absolutely already transforming the way we do business. Whether they consider AI technology to be a friend or a foe, many B2B marketing leaders see the potential—and the inevitability—of AI. In fact, most CMOs in five global markets believe artificial intelligence will surpass social media’s influence in the industry. Nearly six in 10 believe that within the next five years, companies will need to compete in the AI space to succeed.

The Dawn of the Cognitive Era

Joanna L. Batstone, PhD, Vice President and Lab Director at IBM Research Australia and Chief Technology Officer, IBM Australia and New Zealand, says those involved in serious information science understand the enormous potential of intelligent systems.

“Cognitive computing systems learn at scale, reason with purpose and interact with humans naturally,” Batstone explains. “They learn and reason from their interactions with us and their experiences with their environment.”

Intelligent systems can go beyond answering numerical problems to offer hypotheses, reasoned arguments and recommendations. However, Batstone reassures anyone who might still be nervous about the nature of AI.

AI Is as Much About “Nurture” as “Nature”

But don’t worry, AI marketing (AIM) isn’t putting human marketers out of work anytime soon. Instead, it has the potential to be the connective tissue among martech systems, augmenting humans’ ability to make sense of and take action on data.

Wayne Sadin, Chief Digital and Information Officer at Affinitas Life, says, “Humans are still very much driving the train. It’s just a much faster, more powerful train now.”

Sadin urges marketers to rely on machine learning to perform rote tasks (like watching social media posts) in order to free teams to do higher-level creative work. By interconnecting social data to web analytics to a CRM database to external data and more, B2B marketers can use AI applications to automate and personalize many interactions that used to be time-intensive and far less efficient.

For this reason, Sadin thinks of the “A” in “AI” as augmented instead of artificial. “AI is part of the trend towards ‘Augmented Everything’: brains (AI), muscles (robots), vision (AR/VR),” Sadin says. “It makes workers smarter, stronger and faster. It’s not some central overlord machine, though. It’s just smart people taking advantage of data that’s already there and intelligent martech that is getting more and more capable of adapting to changing customer behaviors and expectations.”Sadin cautions that AI has to be carefully nurtured and guided. It can only do what we tell it to do and learn what we tell it to learn. AI can’t connect data and martech systems on its own without a human telling the technology how to make the connections and what to do with the data it takes in. (Maybe Maciej Ceglowski puts it best: “I find it helpful to think of algorithms as a dim-witted but extremely industrious graduate student, whom you don’t fully trust.”)

To train AI apps to be genuinely useful and not just more chaos cluttering up the martech landscape, we have to tie machine learning to business goals and ethical standards and be very, very specific about the data we feed into the AI to train it. We have to set limits and maintain good data hygiene so the AI makes the connections we want and stays on track. Without reasonably clean, complete data, AI is just garbage in, garbage out. And without encoding careful ethical parameters to nurture the AI’s learning and development.

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AI Marketing Requires a Different Mindset

AI is already proving to be more of a friend than a foe to B2B marketers. To get the desired results, though, not only do marketers have to properly nurture AI technologies, we also have to embrace their potential—even when there’s the possibility that AI will eventually render our current jobs obsolete.

Paul Greenberg, independent consultant and author of the best-selling book CRM at the Speed of Light, points out that marketers have to embrace a very different mindset moving forward. Marketers are trained to target personas—representations of broad groups of people with similar characteristics and drivers—and produce content that appeals to them. But now customers expect an extremely high level of personalization and real-time interactions with brands across a multitude of devices and channels.

These technologies will nevertheless grow in popularity. Greenberg expects these applications to be acquired by, and absorbed into, big marketing clouds like IBM, Oracle and Salesforce, so you should expect to see them soon in your martech portfolios if you don’t have them already.

As for what we can and should expect AIM technology to do today and in the future, Greenberg points to one of his favorite marketing videos of the past few years, Corning’s “A Day Made of Glass.” This video was not produced using AI, but it’s the kind of thing Greenberg believes we can and should be leveraging AI to create. He says the Corning video brilliantly connects with consumers’ emotions to create a human-centric vision of the future with extremely broad appeal.

“AIM technology can already do this if we ask it to. It’s not way off in the future,” Greenberg says. “Intelligent systems can already make the connections between systems of record and systems of engagement to understand what would emotionally engage people. These technologies can independently test and learn from people’s reactions enough to change their approach and build highly personalized, relevant and contextual custom content for prospects and customers in real time.”

So is AI a friend or a foe to B2B marketers? The answer is yes. AI is what you make it. It all goes back to how you feed, nurture and train your intelligent systems. Just as you wouldn’t toss a five-year-old child into a mosh pit to learn how to dance, you can’t leave AIM technology on its own to learn from unlimited inputs and “dirty” data sources. If you train it well and use it to build interconnections across your organization and beyond, AIM can significantly augment your human marketing team’s capabilities to anticipate and connect with much larger and more diverse audiences over time.

Source: Artificial Intelligence Potentials in B2B Marketing – D&B

Retargetting is so Flintstones



By Charlie Tarzian, Founder, The Big Willow

So we’re at least 7 years into exchange based media and we’re still complaining about retargeting. Consumer complaints are that it is mindless or creepy. And on the professional side, clients want more control over who to retarget and when.

Meanwhile, back at the zombie ranch of retargeting there has been very little innovation or progress made on some basic requirements that would change the game.

The biggest issue is lack of integration into the enterprise. And by enterprise I mean those data repositories and systems that run any company. The fact that brands continue to chase us with acquisition based messaging even after we have purchased is clearly a missed opportunity. Which begs the question: Is retargeting that misunderstood that it falls to the bottom of the data integration wish list? Do brands understand the magnificent fail of not knowing who their new customers are and the state of play between any one consumer and their company?

Without question brands need to start paying attention to this continual consumer aggravation.

Recently, a B2B client said in a meeting: We are only really interested in investing in our targeted client list. We want to know when they come to our site, we want to know when we serve them ads, when they open and click through our ads, when they follow and share our social links, etc…

So why, she asked, are we retargeting everyone that comes to our site? Our targeted list represents less than 10% of everyone that comes – so why can’t we suppress retargeting to the other 90% of the audience we are not interested in at this time? And what about if we want to retarget based on which part of the site and which product they were engaged with?

Her company’s agency responded: That’s not how it works. There is no way to discriminate. Anyone that comes to the site becomes part of the retargeting pool.

So – indiscriminant retargeting is what it shall be!

Now, on the other side, retargeting relies on building sizable pools of audience to drive the cost of bidding down – meaning the more you have in the pool and the more you have to choose from the better chance you have of winning a certain percentage of your bids and of keeping the costs down. Retargeting buys can be two times the cost on a CPM basis when compared to straight CPM buys. We get that. But retargeting parameters should be no different than how you would set up any DSP-based campaign. You should be able to create whitelists with rules we use in any campaign: only these IP addresses, or these devices or cookies, or customers that have contracts coming up, etc… I only want to target those and with the right context.

If you think about it – instead of relying on the primitive, non-evolved way retargeting is done today, we should be thinking about moving the heavy lifting of retargeting to the same data-driven approach we take through our DMP’s-to-DSP’s-to-ad servers process. That’s how we operate the foundational aspects of our media stack today, so why can’t we use the same stack to inject logic, filtering and knowledge into retargeting.

I can tell you we are working on this issue and I have to imagine others are as well. We call it Filtered Retargeting and to be honest – it is not retargeting as much as it is sequencing messaging based on using historical data. Historical can mean 10 minutes, 10 days or 10 weeks – but the strategy relies on being up to date with previous interactions across data sets and systems. But that is just one dimension.

The other is getting client organizations to architect how key customer data gets into the marketing stack with the aforementioned frequency. When someone makes their first purchase, reactivates, buys a new service, upgrades, etc… the marketing operations world must be updated and rules put in place to allow a change in how we communicate to that individual and/or company. This is the promise of both DMP’s and of an ALWAYS ON marketing stack.

All to say, retargeting has withered on the vine for so long and yet could be so much more effective in enhancing relationships.

Let’s put some of that great thinking that has created so many innovations and breakthroughs into this issue so we can stop talking about it. Selfish as it is, I am tired of retargeting being the subject of dinner party conversations!

What are your thoughts? And who do you think is and/or should be solving for this lack of progress?

Applying Digital Marketing | Happy People | Stronger Brand

MANY years ago, marketers would invest in massive advertising campaigns with headlines like “When EF Hutton speaks, everyone listens” and convince customers that their broker was the best in the business.

TODAY, customers drive the conversation and ultimately the brand. As an example, a happy or angry customer can pulse into conversations over social media with rave reviews or complaints about your brand to millions of people who in turn can have the power to exponentially impact your brand in either a positive or negative direction.

At every stage of customer engagement there exist opportunities to create advocacy around your brand. Companies are just beginning to realize that there are relatively simple ways to utilize digital marketing tactics to improve the overall experience that people have with their brand.

5 simple ways to apply digital marketing to drive improved customer experience:

  1. SEO – Use search engine optimization to help companies find your Contact Us page.

  2. Retargeting – Serve engaged visitors with progressive profiling forms like surveys.

  3. Analytics – Use analytics to track, map and predict how customers contact you.

  4. Testing – Test landing pages to optimize your sales and marketing objectives.

  5. Mobile Apps – Encourage your customers to install your mobile apps.

Ultimately, efficiencies are what drive business decisions. From a cost perspective, digital marketing is the most efficient channel through which to drive new customer acquisition, improve customer retention and  and expand existing customer relationships. Applying these digital marketing principles throughout each stage of engagement will ultimately enhance your customers’ experience and transform your business into one that is more agile and able to react quickly to the changing needs of your customers and future market opportunities.

With the #digital #revolution in the rearview mirror now, for many organizations that were quick to adapt to change during the first decade of the new millennia, firms are now focused on their digital evolution.  So the good news is that there is time to catch up for those firms that were late to the show.

#Happy #marketing, happy #customers.