You Call That Artificial Intelligence?

October 25, 2018

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 and 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.  Policy and practice are close partners in the perpetual dance of future alignment toward more pervasive Intelligent Automation.

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, templates and workflow systems, tuned over time by user experience. Recent advances in cheap 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 5,000-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 our 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 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! We 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 implements 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: Fan Foundry excels at this.

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

DARPA Perspective on Artificial Intelligence

Article: The Sales and Marketing Alignment Conversation

 

 



The ROI of Social Media

October 12, 2016

reposted from Oct 2015

There are two ways to measure social media ROI: (1) direct profit that results when people act on an offer you publicize on a social channel (a promo code, a coupon, or the like); and (2) the contribution to profit and value that results from people engaging on social channels to chat, research, converse, and generally form a positive impression that inclines them to buy, recommend, follow, and stay loyal and satisfied.

Social BI cover

Click to view on SlideShare

We help clients focus on that second, far more lucrative metric, also known as Customer Lifetime Value, or CLV. Ever heard of that? It’s a measure of the profit you can expect to generate from a customer as long as they remain a customer. It includes initial sales, renewals, upgrades, referrals, and other sometimes non-monetary indicators of buyer satisfaction.

How do you measure contribution to CLV? The slide deck linked here offers a glimpse into some of our client work that answers the question.  If focuses less on the technology that underpins the effort, although we do provide a resource list, but more on the types of things you can measure and the ways you can capture the upstream inputs to do that measurement so you can determine what works and pivot to do more of that.  We hope you find it helpful.

How do you measure social media ROI? Love to hear your stories.  Comment below, or really open up the chat by sharing on your favorite social channel!

Cheers,

~Ed


Which KPIs to Measure, and When

January 14, 2016

Maybe you’re the CMO (Chief Marketing Officer), the Chief Sales Officer (CSO), or the one doing it all (sing: C-I-E-I-O). In any case, you are deeply involved with setting strategy, goals and KPIs that will help you make your number. Which measurements matter most, and why? Are you swimming in data and metrics, and confused by the options? You are not alone. Here’s why, and how to solve it.

Today, almost all of a buyer’s journey happens online before they speak with your company.  Often you aren’t even aware, although that can be fixed too (separate forthcoming post; follow this blog).

This means Marketing and Sales have to jointly engage potential buyers over a longer period of time, using multiple touchpoints, to reliably focus on helping the most needy customers and likely buyers.

Geting Organized

Knowing what to measure, and when to measure it, for each Tactic (video, whitepaper, etc.) and each Buyer Journey stage (people ask different questions as they proceed through to a decision), helps you optimize your relationship building efforts and improve sales and service.

The dizzying array of measurements and KPIs (Key Performance Indicators) often hinders progress, so we have reviewed the results of a number of client engagements to bring you an easy single-page reference table that you can use with any CRM system to guide your setup of meaningful measurements, accurately gauge progress, and know where your next sale is coming from.  Your own circumstances may be unique, but this is a start.

A Handy Funnel / KPI Planner Tool

Marketing Funnel KPI clip PreviewClick the spreadsheet snippet here to preview a .pdf of this free organizer tool that guides you through the most important KPIs to set for each Funnel stage, each Goal, and each Tactic you use to make customers and happiness happen. Sales and Marketing people across a number of client projects have tried this tool and liked it.

Get the Actual Working Tool – it’s free

The native file is much easier to work with than the Preview.  It is an ordinary Excel spreadsheet, and I have pre-set it with split windows so you can scroll right to reveal over 30 KPIs that apply for each Stage, Goal and Tactic, without losing sight of the main row and column headers. Check the last box on the list on this online order form to order your free copy.

Get the KPI planner tool - free

Over to You

Try it! I welcome your reactions, comments and suggestions. This KPI Chart will be added to our Resources page shortly, after it has been “out to play” among you for a little while and we have gathered your feedback. Of course, you will be notified of those updates, if you have downloaded the file.

As always, we couldn’t do what we do in this blog without your input, and from the valuable experience we gain working with clients and the many CRM, sales force automation and “social hive” tools we implement for them, too numerous to mention here.  Thanks!

Cheers, ~Ed


The Real Meaning of CRM

November 11, 2015
human and robot hands

Credit: Phillipedia Files

I often joke with clients and audiences that the acronym CRM may be widely accepted as shorthand for “Customer Relationship Management”, but we know what it really stands for: “Can’t Remember Much”.

Before you dash away from this article thinking it’s all jokes, let’s analyze the kernel of truth behind that chuckle.

Some parts of your work could be automated.  CRM is just one tool. That’s the good news. Implemented well, CRM can free you to spend more time applying your expertise on more creative work and expediting decisions on exceptional cases instead of tedious, rote activities like cataloging and retrieving information.

Take the free CRM Readiness Assessment

The main challenge is human adaptability. It is natural to find comfort in routine, but when that same routine becomes unnecessary or a competitive disadvantage, you must adapt or face potential loss. Buggy whips, anyone?

To be sure, the economic benefits of automation include labor savings, but nobody is suggesting that all human-involved work goes away. Instead, your work might become more cerebral in nature. Amazon’s Kiva warehouse robots can stock shelves and fulfill shipment orders far faster and commit fewer errors, and Quill can produce narrative reports from raw data whose resulting output is hard to distinguish from a human-authored prose piece, but they are not existential threats.  Your ability to create, decide, interpret and act on information is a product of your judgment and experience; analyzing the risk and opportunity inherent in any decision is downright, intuitively messy. And we humans are surprisingly, inimitably good at it.  We just need our CRM solution to have proper care and feeding, including clean, accurate, relevant data, so that we can validate our decisions against … something.

It’s not just low skill, low wage work that could be automated. Many highly skilled types of work could have aspects of certain work processes delegated to automation. Scheduling, producing reports and aggregating data can be automated to synthesize new discoveries, flag exceptions and highlight decision options directly at their point of use – – the factory floor or the boardroom – where a judgmental human can use discretion to suit the desires and needs of a customer.

What does this mean to the business leader? It means we need to use our creativity and judgment to study developments in new automation solutions and assess how and when we might sensibly adopt them to maintain a competitive edge, or perhaps or discover a new one.

Technology of any kind is usually only a temporary advantage, but human creativity and productivity are hard to beat. You definitely want more creative humans on your team – especially creative ones who can interpret your needs and help you find the automation solutions to fill them. That’s where a CRM expert comes in. Shameless plug alert: luckily, you found us.

Additional Resources

Four fundamentals of workplace automation (McKinsey)


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