You Call That Artificial Intelligence?

While attending a recent Salesforce.com Basecamp for Customer Service Pros conference here, I was particularly taken by a keynoter’s observations on our collective progress toward incorporating AI into business software like CRM.

Later in the conference, while viewing some of the product demonstrations, wherever the word “AI” appeared onscreen, I or someone would poke their hand up to inquire; we were almost uniformly answered with some variant of “it’s coming”.

For all the hype around AI, the nearest we have come is in programming our systems to model best practice, then prompt users in performing patterned workflows that hew to that programmed best practice.  Call it computer-assisted pattern recognition, or Intelligent Automation.

This is not AI, but it’s a start. Using DARPA’s definitions of the Three Waves of AI, it appears many of us are still broadly in the early “First Wave of AI”, in which human-composed (hand-cobbled) workflow rules guide software users and customers through choice architectures with prescribed, rule-based workflow steps. We can perceive patterns, then use reasoned judgment to either follow the pattern or justify exceptions. If exceptions to policy or rules are frequent, then the policy is adjusted to reflect the pattern of practice, effectively updating policy to more closely match reality.  Policy and practice are close partners in the perpetual dance of future alignment toward more pervasive Intelligent Automation.  That’s the thing about a policy: its highest use is to justify exceptions.

AI Wave Number One: Handcrafted Knowledge

Calling it AI is, in my unvarnished humble opinion, a bit flamboyant. In truth, our “Artificial Intelligence” is stuck in the previous century, at DARPA’s “Wave Number One”, where a PC could recognize our basic input patterns (if x occurs, y is likely to follow), and reflect those patterns in tools like spellcheckers, autocorrect and autocomplete, aw well as templates and workflow systems, tuned over time by user experience. Recent advances in cheap storage and processing, distributed data and voracious coding have improved matters to where a user can create workflows in a codeless, drag and drop fashion. Twining together all those 7,000-plus pieces of commercial marketing software is everyone’s grail quest – and there’s even an app store for it. Hello, Zapier.

Today, our systems can support human ability to perceive and derive value by improving our reasoning and judgment, spotting trends, and drawing inferences based on historical or near-real-time data flows.  This is where the largest untapped opportunity looms for organizations to achieve savings through efficiency by tuning their tech stack in sales, marketing and service.  People and time do not scale, whereas a system can instantly scale to distribute workflows and data interpretation to any number of customer facing people, and even extend that capability into the hands of customers themselves.

Is your business technology supporting you in this way? If not, consider yourself a laggart in danger of losing big. Put simply, in life there are 3 types of people: those who make things happen, those who watch things happen, and those who wonder what just happened.

Today, thanks to cheap computing, massive data “blooms”, and distributed networks, we can now amass, consume, configure and present interactive display reports on top of large datasets to help us understand it in self-driven configurable dashboards. Get some! (Shameless plug alert: FanFoundry can help).

AI Wave Number Two: Statistical Learning

What’s coming? Looking again at the DARPA definitions of the 3 Stages of AI, we can next expect to see engineers creating statistical models for specific problems and training systems to solve those problems, once again using big data as the source material for the training exercise. Even this stage, however, has its limits. For example: Showing a computer thousands of cat photos can eventually train it to recognize a cat with high accuracy – not flawlessly, but reasonably well. Consider, however, that a 3-year-old child can recognize a cat flawlessly after only meeting the family cat and the neighbor’s cat, and looking at a sketch drawing of a cat, and will point to the cat cartoon and say it’s a cat. Thanks, brain!

Computers, meanwhile, face challenges in recognizing a handwritten number 8. The myriad of writing styles, speeds and writing tools further confounds the problem.  This diversity of inputs and human approaches is the biggest challenge to UI developers.  Confusion over the validity of our databases is often caused by uncertainty about what the user intended to do or say when they input their data.

A slight 1% inaccuracy of input today can result in an outsized unreliable output. This is also the stuff of internet memes and fake news. Anybody can publish a single tweet to a vast global audience. The pace at which all that published-rubbish (“pubbish”?) speeds past us confounds our efforts to filter and validate truth. Our resulting, collective judgment errors can result in an outsize misinterpretation of fringe views as central guidance. Absent a moral compass, a distorted maniacal map could lead many, unaware, off an ethical cliff. Upshot: to trust your data, you need to regularly audit.  Shameless plug alert #2: Fan Foundry excels at this too.

Wave Number Two will take some time to get right. I’d give it a decade or two to reach prime time.

The Third Wave of AI: Contextual Adaptation

In this future (certainly not the present), systems can reliably explain real life phenomena. They can perceive, learn, reason and even abstract. They can predict success or failure. They can understand why or why not. They can know why you made a mistake, when to trust your judgment, and can guide you on that optimal path of interpretation and judgment.

The big challenge here is for us to surrender our trust to a cyborg partner. For now, though, it’s a bit out of reach. To quote the articulate supercomputer HAL from the movie 2001: A Space Odyssey: “Sorry, Dave, I can’t let you do that.”  Codicil: “Not yet, anyway”.

What’s your Sales, Marketing and Service challenge?  Does it involve people, processes and technology?  Perhaps we can help.

Recommended reading

mAIcon 2019 keynote with Karen Hao: What is AI? (YouTube, 30:00)

DARPA Perspective on Artificial Intelligence

Article: The Sales and Marketing Alignment Conversation

 

 

CRM Pro Tips: Thinking about Linking


chain-linksDear CRM user: This is arguably the most important 5 minutes of CRM training you’ll ever need, if you want a CRM that is well-tuned, delivers on its promises, and gives you unbeatable competitive advantage.  ~Ed

Human intelligence is often described as sophisticated pattern-matching or linking concepts together. Example: you learn early in life not to touch that hot stove a second time. (“Thanks, brain!”)

Everything we do is linked to something else, somehow. Our “cause and effect” knowledgebase can be expressed as “If / Then”: If X happens, Y follows. We learn and improve by linking new ideas, events, data and relationships.

CRM, similarly, unlocks tremendous potential advantage, helping you to link activities, people and resources with deals, customers, relationships, and reliable dashboard reporting.  Done well, it helps you discover unique and repetitive link patterns and accelerate improvement in sales, service, revenue and innovation.  You can then detect patterns in buyer behavior, purchase process, dealflow and more, which in turn can improve your forecasting accuracy and your business intelligence advantage.

The reverse is also true:  done poorly, your CRM database becomes a useless mess of disjointed data, and your team coordination, customer satisfaction and data intelligence can suffer.

This 15 page playbook illustrates in just 5 minutes how CRM products are ready-built to help you leverage links and relationships among people, data, sales, products and more.  It all comes down to “thinking about linking”.

 

Have at it!  I welcome your reactions, comments and edits.  Help keep this crowdsourced tutorial fresh and improved.  Of course, I’ll credit you with any changes that are kept.  More CRM Pro Tip playbooks to come.  Subscribe! It’s all free.

Cheers,

Ed

Prevent a Marketing Automation Shipwreck

Fifteen years and 40 client projects later, we have seen some Marketing Automation (MA) and sales CRM implementations deliver significant revenue improvement for some clients, while others have struggled to achieve break-even.  Some clients have become top performers, while others are challenged to adapt.  What made the difference?

The answers can be sorted out three ways:  expectation, preparation, and perspiration.  Here we focus on the first issue:  Expectation.

shipwreck

The Challenge of Change

Marketers usually enter a Marketing Automation (MA) implementation expecting to improve multi-channel communications, streamline email marketing, analyze response, centralize data, prioritize leads and meaningfully engage buyers throughout the buy cycle.

All this is possible, and more – assuming you expect deeper changes to business processes, which is where the greatest improvement opportunity exists.  Hint: If you don’t have processes in place, but expect your new Marketing Automation solution to solve that, it’s not a good fit.  Technology probably won’t help, simply because you cannot automate a vacuum.  In that case, you might instead consider a “readiness” project involving an audit of current information flows and workflows, along with recommendations for adapting to keep pace with customer needs and competitors. We can help there.  Try taking this self-assessment, for starters.

Perils of Not Changing

If you have rather well instituted processes but you don’t plan to examine process change opportunities during your MA implementation, preferring instead to have your new system mirror existing practice exactly “as is”, perhaps expecting that this path-of-least-resistance approach will ease implementation or make it more palatable to users, you may expect to take longer to see a return on your investment – and you may even have difficulty measuring it.  For example: using MA to do “batch and blast” email doesn’t leverage the technology, and you will likely miss out on the benefits of data analytics and audience segmentation available with most MA solutions and which could improve your audience response rates, shorten sales cycle time, and accelerate ROI.  Our top performing clients generally see this new “software layer” as a source of innovation and continuous, positive change.

deckhands

Downstream Effects

Marketers need to have reasonable expectations regarding the nature of workflow and how it could likely change.  Marketing Automation doesn’t always reduce the burden, and could actually increase it.  For example, the new software can be difficult to learn.  It often demands new content, or at least changes to existing content. It makes good/bad results more visible.  It often requires new skills, new ways of thinking and, consequently, changes to workflow. It requires flexibility and adaptability to make refinements as new discoveries occur.  It is, in other words, disruptive in many positive ways – but only if you the resilience to maintain a positive focus and the mindset to adapt.  This points to a need to communicate early and often to your organization and audiences about your marketing automation implementation, to avoid surprises and disruptions downstream. In short, it’s relatively easy to change systems, but not so easy to change people.

Three big wins

Some of the greatest improvement opportunities in MA and, not too coincidentally, the three areas where the learning curve is most intense, are the areas of lead management, response triggers and workflow.   All three involve close collaboration among many internal stakeholders, starting with marketing and sales, but often expanding to the service and product teams, and to your executive team who consume the reports based on the complex information flows within your MA technology.  Expect, therefore, that your internal processes will be laid bare and examined closely by multiple stakeholders.  You all stand to gain from this new openness.  This is another great reason to widely communicate about your MA implementation plans, with an eye to extending its benefits to all your stakeholders.

You should expect to assume the role of chief communicator on behalf of all parties, which means more work for you, but the results can be well worth it.

Customers Weigh In

Customers and buyers, meanwhile, have new, more sophisticated expectations.  Just a scant decade ago, Sales and Marketing were the main information gateway for buyers.  Today, by contrast, a buyer can be substantially finished researching a purchase before you even become aware of their interest.  What are you doing to help nurture those potential buyers and help them buy?  How effective are you at competitively positioning your products and pricing?  Marketing automation solutions cannot fix a problem concerning product, price, competitive position, or flat-out bad marketing.  Be honest with yourself about other shortcomings, and consider fixing them first.

Seek Counsel

Finally, it would be prudent to discuss your plans with someone experienced in marketing and sales technologies including SFA, CRM, marketing automation, email marketing, and mapping  their related business process flows.  You could gain perspective on the challenges and opportunities a marketing automation solution can offer.

How does your experience compare?  Is your marketing automation delivering its expected results?   We  welcome your comments, ideas, tips stories.

If you have questions, feel free to contact us.

Marketing Automation: Masters of the User-verse

The customer is King, but Users are your Universe – your “User-verse”.   How do you stay at their center?

According to Forrester Research, by mid-decade over half of all purchasing will be done online.   For post-digital people (think: Millenials & their iGen progeny), who represent the incoming wave of buyers, influencers and decision makers, this has already come to pass.  Millenials are comfortable with technology; iGens are uncomfortable without it.  Today’s post-digital citizens deftly filter and apply information to move smartly through life.   Socializing and transacting online is ordinary and commonplace.  Today’s cadre of decision makers, too, use mobile and social filters to navigate decisions and find relevance in the bit-torrent of change.  Collectively, we are your expanding User-verse.  For us, B2C and B2B are becoming less different.  Now it’s U2E (Users to Everybody), and therein lies a challenge: filtering and relevance.

The challenge is especially acute for Marketing leaders, who are now being held accountable for ROI while also striving to maintain respect and relevance with audiences.   Some organizations do a great job at meeting the needs of our always-on audience. I call them Fan Foundries.  We recognize them by their digital presence in our lives: everything real-word is mirrored and ehanced online, where it can be detected and consumed by customers, suppliers, employees etc.  In turn, our digital travels are observed by these smart Fan Foundries to determine how best to help us through our decision journey and, where appropriate, engage and buy.  You know you’re dealing with a Fan Foundry when your next interaction feels like a continuation or enhancement of the prior one, rather than another blind date.

How are you doing?

How is your organization doing?  Are you at the center of your Userverse?  You probably know that answer, but try this experiment.  Visit Amazon, iTunes, or some other online account you admire.  Compare that online experience to that of your own business.  If you don’t measure up, be assured somebody is going to steal your business soon.  How soon?  How about…while you’re reading this?  If you’re still doing mainly interruptive, outbound marketing, yet your audience is filtering out your messages (via spamblock, TiVo, Unsubscribe, delete key, etc.), what are you doing to help yourself get found and stay relevant?

Fortunately, you no longer need a massive budget to master your User-verse.  What, then, do you need?   What does a balanced, humming Fan Foundry look like?  Layer by layer, it might resemble this:

A Marketing and Sales Governance Model
click to enlarge
  1. Front end – Web interfaces (desktop, mobile, kiosk, email, social media, etc.).   The online experience these days is spotty at best, but many good examples exist and they’re in plain view.  Good poets borrow, so why not learn from the best, then adapt and refine it based on what you learn from your User-verse as they navigate your content, make choices, and send you signals about what they buy and why.
  2. Content layer – main website content, product/service literature, user-generated content (reviews, comments, etc.), custom apps, partner portals, blogs, e-newsletters, online forums, social media, customer care & service channels, etc.   Rich content, re-formatted for channels and micro-audiences, is a golden opportunity to anticipate and delight users, keep you appropriately centered, and signal you on when and how to engage.  Just like your web navigation, your content navigation can be tested and refined based on user behavior.
  3. Information management layer – CRM, marketing automation, analytics, modeling, planning, supply chain, financial datastores, etc. Here, with an array of connected technologies, you can dashboard, orchestrate and analyze the flow of people, information and material to discover competitive advantage and facilitate progress.  Don’t let the geek factor frighten you from implementing some basic, essential tools.  Dig in and ask for help. Or not.  And be toast.  (Suggestion: call us)
  4. Records/data layer – In an age where more and more data is publicly available and public-generated, your ability to harness data to learn and adapt more quickly could spell success or failure.  Master this layer, and you can spend more time selling, transacting business and nurturing future customers while cutting out time-wasters.  By cultivating your own data sources and applying your own relevance filters you can speed learning and adaptation, and improve your ability to reliably forecast a profitable future.

What stands in the way of progress?  The usual responses are resources, people, skills, time, money, and appetite for change.   Okay, but wouldn’t you like to delight customers and win new ones?   Wouldn’t you like to substantially and sustainably grow revenue? Wouldn’t you like to still be in business and growing – or, if losing, at least know why you’re losing so you can adapt and improve?

If the answer to any of these questions is yes, and you just need resources and expertise to make it happen, contact us.

 ~

Get started today! Visit our Resources page to download free planning tools.