The CSI Guy – Customer Success Investigator

sherlockRecently I read a fascinating article on how crime investigators are using machine learning to find patterns and uncover insights that otherwise wouldn’t be detectable.   Investigations ranged from criminal to cybersecurity, competitive counterintelligence, and corporate litigation.  In one example, a firm showcased how – if this technology had been available during the Enron era – they might have proactively detected the scandal, potentially averting the crisis.  Their demo traversed 500,000 Enron emails, and as it did it learned how to flag suspicious ones.

It’s not news that pattern detection software works for fraud detection.   For years, banks have employed systems that scan structured credit card transaction data, and flag unusual activity.  Yet what occurred to me is this same approach and its specific techniques are extremely well suited to the art and science of developing customer intelligence against unstructured big data.   Customer experience pros could then unlock new mysteries, and take appropriate actions leading to great customer success outcomes.

The first thing criminal investigators do is they gather all the facts they can, from any available source – Emails, phone records, texts, web activity.  The adage being “Leave no stone unturned.”   It’s never clear at the start of any investigation which clues might matter, and may link to others – so all are important regardless of their form.    As the investigation unfolds, machine learning techniques, such as neural networks that use self-organizing cluster maps (known as SOMs) can help find patterns, and eventually help the investigators form a hypothesis.  Available evidence is used to test whether the facts fit the theory.

Shifting the frame of reference, gaining customer intelligence and using it to solve for marketing and customer experience challenges can benefit from this same methodology and technology:

  • Consumers leave clues about their preferences and behavior in many places; sometimes in unstructured forums, like social media, product reviews, and blogs.
  • It’s virtually impossible to sift through this data without the aid of technology and automation.
  • Machine learning can be used to find patterns in customer activity, such as what product they are most interested in buying, or that their sentiment is trending toward total dissatisfaction.
  • Once patterns are detected, predictions can be made and actions triggered in efforts to anticipate needs or alleviate matters.

As a consumer, my natural reaction might be to say, “That’s creepy and spooky”.   Ironically though, most firms simply want to use this to improve your experience with their brands since they know it’s critical to their health.  Repeatedly, surveys show above price and product, people leave because of dissatisfaction with the way they are treated.

But the level of dissatisfaction is qualitative and differs by customer.  One customer who experiences a single network issue may become enraged, while another may be more tolerant.   Knowing this and the value of each customer helps the company treat each situation with a custom tailored response.

That all sounds like common sense and easy, right?  Try doing it on millions of customers, with billions of bytes of unstructured data in their direct conversations and behaviors, and their indirect musings on social media, in blogs, and elsewhere.   Moreover, try to learn when each customer reaches various stages of interest or displeasure, and overtime improve your ability to predict these and take timely action.

Since the dawn of time, we learned that to survive we needed help from machines.   Use this newest breed of machines along with time tested investigation techniques to crack the enigma of your customers, gauge their state of mind, and delight them with personalized experiences.

Note:  These views are my own, and not that of my employer

Incremental contextual marketing for the distracted consumer

Consumers today are distracted and so I’ve coined a new term describing how to reach them: incremental contextual marketing.   The idea came to me by when considering the mental diagnosis of ADHD, and then drawing parallels to phenomena observed in modern consumer behavior.  In this blog, I explore this and then unveil some thoughts on how to best approach it with marketing techniques.  And I’m going to try to do all that in a short blog, because…well…read on.

Blame it my ADHD

“I feel like I’m from a different planet.”  Years ago, this statement might have been uttered by a person diagnosed with ADHD – Attention-deficit/hyperactivity disorder.   Yet, it’s how I feel today when I compare myself to the average modern day consumer (is there such a thing?), with their impulse decision making, short attention span, and lack of focus.  Does everyone have ADHD?  Of course not – that’s a real mental disorder, and not one to poke fun at.  But call me crazy because when I consider an important purchase, investigate a brand, or generally try to write about something or solve a problem, I take a deliberate approach, use critical thinking skills, do in-depth research, triangulate sources, and plan ahead.  One thing is certain – I know I’m from a different era.

Brain with ADHD

Consider this definition of ADHD from the Mayo clinic website:

“ADHD is a chronic condition that includes a combination of problems, such as difficulty sustaining attention, hyperactivity and impulsive behavior.”[i]

Or this about those with ADHD by William Dodson, MD from ADDitudemag.com:

“The ADHD world is curvilinear. Past, present, and future are never separate and distinct. Everything is now. ADDers live in a permanent present and have a hard time learning from the past or looking into the future…”[ii]

Sound a little like today’s in the moment consumer with a gold fish like attention span, who expects instant gratification and exhibits spontaneous buying behavior?   It’s no secret; the world we live in promotes and fosters this behavior.

  • Consumers are generally impatient and hyperactive. They get upset if they are in any line or have to wait for anything for more than a few seconds.  They are upset if businesses don’t remember them.
  • Consumers can’t focus. They are constantly interrupted or busy with smartphones, multiple devices, packed schedules, and keeping connected with extensive networks.   The average user checks a phone 150 times per day[iii].
  • Consumers live in the moment. They quickly forget their own loyalty history (or lack thereof), and often inflate their true propensity to do something in the future.  They expect their present context to be understood, catered to, and appreciated.

Is there a cure?

Although you won’t change this conduct, you can still accomplish your goals by employing a best practice I’ll term incremental contextual marketing.   As a marketer, accept that there is very little patience, increasingly shorter message shelf lives, and a consumer that is less and less receptive to any outbound marketing, or any message for that matter that is too long or ordinary.   Make no mistake, you can still build brand awareness and garner loyalty – however realize two things:

  • It can take years to build and establish loyalty, yet with one bad experience it can evaporate in seconds, since a consumer’s mindset is, “What have you done for me lately?”
  • You need to message in waves; in small compelling quickly digestible chunks available in any channel.

On the second point, and this is key, even if you have a deeper, more complex, longer term idea that you need to explain or impression you want to make, break it up, and message it over a period of time.   Incremental contextual marketing means both repeating and/or building upon your message, always using current consumer context to reinforce, sustain, adjust, and evolve it, with the end result being a better educated consumer, more likely to remember and to be impressed.   This approach works for marketing a product, educating a consumer on your services, or surveying them for preferences.   The stream of tactics used can be repetitive or additive depending on the goal.

For example, if your primary goal is brand awareness, a repetitive message is fine, but don’t repeat it in the same slots, at the same times, using the same channels.  Mix those up.  Make your points proactively to consumers in their preferred outbound channels, with the same messages available to them when they are in-channel.

If your goal is educating the consumer on retirement strategies, run a series of messages that build on each other, with each subsequent message summarizing key points from the latter, and then appending new ideas.  Use current context to adjust the message, if for instance, the consumer has clearly become interested in college savings plans.  The trick is for each message to be randomly incremental (without a predictable rhythm but still a sustained undertaking) and conversational – strategically placed in varying media at a calculated (but somewhat random) cadence so as to optimize its movement from short-term to long-term memory.  Use storytelling and make it relatable in its tone.   I learned the effectiveness of this method a few years back when I embarked on learning French as an adult – That said, I think you can be much more effective that I was in becoming fluent by not waiting too long before you start.

As a firm, you need an approach, a systemic mindset, and technology stack that can react and adapt to this dynamic environment.  Ironically, some of the same technologies that may be reinforcing this behavior can be used to combat it.  Together, the total solution has to be customer focused, concise, real-time (responding in milliseconds since the consumer won’t wait), consistent, contextual, and unified.  It must be unwavering in its ability to identify consumers with pinpoint accuracy, summon a photographic memory of their interests and preferences, factor in their current context and condition, and then act with predictive intelligence, rendering easily consumed yet compelling content, all while still delivering actions with a personalized / human touch.

We live in a fast paced, short story world, with millions of micro blogs (less than 500 words), billions of videos (less than 3 minutes), and trillions of twitter posts (less than 141 characters).  Accept what you can’t change and use the right methods with the time crunched consumer, craftily using bits of incremental air time to make your points.

You made it to the end (a blog with nearly 1000 words…congratulations) and so perhaps you are like me.  For the rest from earth, however, I’ll need more posts.

Comments and alternative views are always welcomed.

[i] http://www.mayoclinic.org/diseases-conditions/adhd/basics/definition/con-20023647

[ii] Dodson, William.  http://www.additudemag.com/adhd/article/10497.html

[iii] Meeker, Mary and Wu, Liang.  Internet Trends D11 Conference.  Kleiner Perkins Caufield Byers (2013): 52

Customer Data & Decisions – “Big Data – Big Value”

In my previous blog (“Big Data – Big Waste?”), I advocated about the importance of an upfront blueprint to help focus big data efforts in areas that lead to valuable insights.  Taking actions on these insights is ultimately how you glean value from your big data.

bigdata_value1

The 5th “V”

Strangely, many who espouse the virtues of big data rarely start by describing the value that can come from it, but instead pontificate about its attributes – Volume, Velocity, Variety, and sometimes a 4th V – Veracity.   Let’s talk about the 5th “V” – Value.

bigdata_value2

What is “Value” really?

Lasting value is created when there is a positive exchange between you and your customer. Yet if you sell something that doesn’t meet their needs, you create the illusion of value, only to see it wiped out later.   Conversely, discovering and acting on activity patterns can lead to explicit and latent needs being met, resulting in customer satisfaction and lasting value.  Tracking big data effectively can lead to these discoveries.

To illustrate, if I observe a customer’s repetitious buying patterns, and then offer to sell products in bundles, bulk ship them for less, or proactively send them, value is created for them – and you ensure a future purchase stream.

Let’s look at some examples of what firms are doing to unearth insights, take actions, and create value.

Real life examples

A leading automotive firm installs numerous sensors in high end vehicles that gather driver data –   predictive analytics warn drivers when fatigue might be setting in.   Farmers use wearables on cows, improving fertility and birthing success rates.

A major online retailer uses purchase history to predict what products you are likely to buy in the future, and stages those closer to reduce shipping time.  A travel site can monitor real-time flight activity, anticipate delays, and notify travelers – often before the airline does.

bigdata_value2b

These are but a few examples of the way firms are already using sensors, streaming big data, finding actionable insights, and creating value for their customers and them.

What should I do?

Ask yourself two simple questions:

  1. Is my company using modern data collection, streaming big data in real-time and using predictive intelligence to understand the patterns?
  2. Are we taking immediate action on these insights to enhance the customer experience?

If you answered yes to the first, but not to the second, you have the infrastructure, but without action will get no benefits.  If neither is true, you are falling behind by the day.  But it’s not too late.  Act now for value.

You’ll need a unified system that can ingest structured and streaming unstructured data, perform real-time analytics that monitor for patterns, decision strategies that arbitrate and trigger the right actions when unusual opportunity or risk is detected – and a system that can also automatically kick off processes to alert personnel, open a case, or notify customers.   Make sure to find a system that can give you this in one platform or otherwise you will waste valuable time implementing, integrating, and adjusting various pieces when you could have been creating value.

Comments and alternative views are always welcomed.

Note:  These views are my own, and not that of my employer

Customer Data & Decisions – “Big Data – Big Waste?”

Part 1 was about what firms really do know about me as a customer. Part 2 covers the ever popular topic of Big Data and why it needs a sponsor, action plan, and a solid analytic platform.

What did you say?

Did I get your attention with my somewhat controversial headline? Maybe it’s actually not that contentious because simply wiring to and capturing lots of data (e.g., Big Data) does nothing for you except add cost if you don’t effectively glean insight from it, and take action on it.   It’s no different than any other asset, in that if it’s idle, it’s sucking energy and not providing any return.   Like a big data black hole, where data enters but no insight can escape. How do you combat that?

blackhole

Have an action plan based on the kinds of customer decisions you want to improve, investigate data required, and constantly test, monitor, and refine that plan.   This plan will dictate what data you should be seeking and exactly how you will leverage it. In other words, work backward from your desired outcomes.

You might also be asking, what is big data? Good question.   As a participant in the business intelligence revolution, I’ve seen massive databases used for years for decision purposes. So what is new and different?   Actually, there are a few things.

First, customer data has been historically captured, scrubbed, matched and restored into on premise structured databases.   This led to the enterprise data warehouse with the so called “360 degree view” of the customer.   These systems required data expert intervention to add new data elements, were usually on premise, and latency rendered the view stale for today’s standards. Consumer and market expectations have evolved to expect on-demand and streaming data reflecting the latest and greatest view of the customer.

Second, since it ultimately required a target structured store, unstructured data, which is massive, became difficult to assimilate into one structured data warehouse.

And third, the variety of structured and unstructured data sources have grown, so much that again using an approach of trying to codify and blend all of that data into one mart did not meet flexibility, agility, and timing requirements of business people trying to make better decisions.

Ok, I need a plan. What next?

What if you could identify and sway vocal and influential customers? What if you could proactively identify customers at risk, and take actions to not only save the relationship, but turn them into ardent supporters?

Take these types of questions, and work backwards to formulate your plan.   Call it your big data blueprint.

worldascpu

Do you already know who the most influential customers are?   If not, start there.   How would you define this?   Conventional wisdom may first suggest it’s those with the biggest network of followers or highest NPS score. But upon further review, what might be more important is customers that actually frequently refer versus ones who say they will.   Working back, you would need data like mentions and referral codes. So determine the particular outcome, and then concentrate on connecting to the data you need to monitor and track those actions – viral actions such as re-tweets, re-posts, forwarded links, reference events, and such.   Then, rate your customers on that basis – building a Clout Score – the higher the score, the more clout they have with others and the more they refer you.   This score is then connected with actual behavior instead of formulations, surveys, or postulates.

Likewise, figuring out which customers are at risk, you might hypothesize that a major service interruption would put them at severe risk, and thus simply being able to run a query to find all customers impacted by key service disruption events would suffice.   Yet often, customer retention risk is much more complicated than that, and it’s likely that in this case you need a behavioral model that considers various risk factors, such as service disruption patterns, social sentiment, clout, customer loyalty, competitive options, and switching costs – and then test that model against real churn outcomes to calibrate its effectiveness.

Having sponsors is vital because invariably some aspects of your big data plan will involve capturing and leveraging data not readily available, and thus sustaining funding and resources to see your project through will require champions – people who believe strongly in the cause, and can help.

What technologies can help me get to my happy place?

We don’t live in a simple world.   We accept that, or get lost, frustrated, and fall behind – but we do expect technology will continue to help us navigate the intricate world.   So we seek the simplest and fastest solutions to complex problems.

Your answer is you will need many technologies. Accept that and do business on that basis. Select your stack based on requirements that your vendors are open, constantly invest in innovating their underlying technology, have exceptional integration both with their own sister products and with the outside world. Consider firms with a robust ecosystem and strong reputation for training, partners, and professional services.

Big data systems involve storage and retrieval of unstructured information, which is data that has not been highly codified from its raw form.   For example, data entered into free form text such as comments to blog posts or data collected from digital activity such as granular website click activity.   Big data is also real-time streaming data coming from various sensors that are always on, and stream data (often 24×7) such as devices that report precise location of objects (e.g., mobile phones).

Partner with a vendor that has solid, modern, and open technology, and has it in one platform. Beware of companies that get the marketing right and have compelling messages, slides, and even case studies, but under the covers have 2 or more actual platforms stitched together, and requires more custom coding to meet your requirements. How ironic that I’m warning marketers to be wary of the marketing!

Comments and alternative views are always welcomed.

Note:  These views are my own, and not that of my employer

Customer Data & Decisions – “Reflections of Me”

In this post, I explore what firms really do know about me as a customer.

reflection2

What do they know, and how did they get that?

Wow! Where do I start?   Many companies today are doing everything in their power to amass as much data on me as possible so presumably they “know me” and make more relevant marketing offers…or as they say, “to provide me with an exceptional experience through an ongoing conversation.”

As empowered consumers, we are the judge of whether they are doing this well. Are they really capturing the right information and in a way that is respectful, well-timed, and used appropriately? This subject quickly stretches into ethical and political implications, but to avoid that, I will just lay out some facts about what companies are doing:

  • First and foremost, they save everything I do with them. All interactions, all transactions, all orders, all clicks on their website – basically any activity on their physical and digital properties they capture and keep – in some cases for 4 years or more.
  • They can often freely share this information with subsidiaries and affiliates (which means a lot of other companies) unless I explicitly ask them not to.
  • They append 3rd party data – lots of it. The sharing of data about me is ubiquitous. Appending means other companies are capturing data and sell it and it’s often indicative of my affinity to like, want or to buy something. This can pretty easily be matched to me with a presumption, for example, I also like to golf because I subscribe to a golf magazine.
  • They are looking at my patterns of activity.
  • They progressively profile through very short but repeated data collecting. For instance, I sign up on a website and provide basic information, then I agree to a news letter, and they capture some preferences, I download their mobile app, and so forth. Eventually, they may know whether I own or rent, have children, or are planning a kitchen remodeling.
  • And they try to predict their next best move. In other words, they are trying to figure out what I really need and want. Called “Next Best Action” technology, and usually found in larger companies, there are very large teams tasked with calculating lifetime value, building rules, testing propensity models – and ultimately a hub that makes promotional, product and service recommendations.

Really very little of this is new my friends, it’s just massively accelerating.   In 1992, one of my favorite non-fiction authors, Erik Larson, wrote a book called “The Naked Consumer: How Our Private Lives Become Public Commodities.”[i] Back then, his impetus for writing the book was based on a pretty simple event driven mailing he received for his child’s first birthday. Intrigued, he chronicled a world he saw as already borderline out of control with consumer data sharing. Imagine his sentiments now with the growth of the internet, digital channels, social, mobile, and big data.   I think he might change the title to “The MRI of the Consumer.”  This month, Scott Brinker posted a blog entry estimating that nearly $22 billion USD of venture capital funding has been poured into the marketing technology companies he pastes onto his marketing technology landscape and admits it’s probably underestimated.

As a long time marketer, I’m not that paranoid or really that appalled at what is going on. I still believe we live in a world that has checks, balances, methods and free choices.   Often, as consumers, we decide how much information to give up in return for something.  In most cases it’s a conscious choice. And there are ways to combat and prevent abuse. My biggest concern is security, as information is repeatedly hacked and then used for purposes it was never intended for. Better security and education are needed, but in general I don’t think it’s as surprising today to the average person as it was for Larson 20 years ago.

But rest assured, this picture of you is getting clearer – and there is a substantial amount of corporate energy being poured into filling in the blanks. The popular term is “The customer journey”, and now also being called “The customer movie”, with the intent to define every frame.

Yet motives and reality are two very different things.   I might want to be rich, but simply wanting doesn’t make it so.   And really, who I am versus what specific habits or preferences I have in relation to a certain product or service is generally where the line is drawn. For instance, a home improvement business would love to know what kinds of building skills I have, what tools I have, and what projects I’m considering, yet I don’t think they really care about what music I like.

What do they intend to do with my information?

I believe at the heart, companies just want to sell more of what they have and do it at the lowest possible cost to them.   It’s that simple.   But they know the world is competitive, there are choices, switching barriers have eroded, and if what they are offering (or failing to) isn’t a match, or at the right price – I will go somewhere else.

So they collect data, study events and patterns of activity, test timing, try to get preferences right, personalize content, and hope I’m impressed when they take actions.event_detection

Are they becoming specialists majoring in knowing one aspect of me, and knowing it well?   Perhaps, but make no mistake their not your best interests are in mind, and if information is useful to another party, and a business transaction makes sense, it will happen. Ironically, businesses are better at sharing customer information then the healthcare industry is at sharing patient information, although finally we are seeing some improvement there.

How did they do that?

It’s really not rocket science, yet amusingly marketers are applying technology that is also used to help launch and guide rockets.

Space_Shuttle

When a rocket launches, there are sensors monitoring all its complex systems. As a consumer, your systems – what you say, what you do, where you go – are being monitored.   Hotels are now placing beacons at key locations such as the front door, to detect when you arrive.   Stores are using similar technology to gauge your potential interest in a product sitting on the shelf you are next to.

There is already software and technology, and the cost is dropping, to gather this data and allow the marketers to access it and build rules on it (e.g., if customer arrives, alert front-desk personnel and pop-up appropriate offers).

Rocket scientists make heavy use of statistics and probability theory to understand the amount of redundancy necessary in systems, the likelihood of something failing, or predictions of weather to gauge best launch and landing windows. Marketers use all these techniques to tune their systems for response time versus cost, whether a new promotion will succeed, or timing a communication.

Also, the cost of storing, aggregating, distilling, modeling, and using this information is dropping rapidly.   The internal discussion has shifted from how much data should be saved, to how more data can be synthesized and insights gleaned from it.

A confluence of freely shared institutionalized best practices, application speed and simplicity, cloud computing, automation, and scientific testing procedures has led to more companies with access to better marketing technology – and a better, albeit still incomplete picture of you the customer.

Comments and alternative views are always welcomed.

Note:  These views are my own, and not that of my employer

[i] Larson, Erik. The Naked Consumer: How Our Private Lives Become Public Commodities. New York: Penguin Books, 1992.

True Omnichannel Marketing – Part 4 – “Seamless Experience”

In Part 1, I explored how and why to test for the right mix of channels.   In Part 2, I covered channel activity coordination and consistency.   In Part 3, I delved into using technology to achieve effective channel integration for optimal marketing decision making. In this post, I investigate the concept of providing the customer with a seamless omnichannel experience.

crosschannel seamless marketing

What is a seamless omnichannel experience?

When you shop, or do business with any firm, I’m sure you don’t think of them as several companies organized by channel. You probably think of them as one business. Yet so many firms still operate their channels by groups that are motivated to improve your experience in that channel, but not given incentive to guarantee you have an exceptional experience crossing channels.

If you are like me, you take a deep breath and hold in a sigh nearly every time you are passed across channels; whether it’s by a human saying they will transfer you, or whether it’s a system, such as an IVR.   Basically, you have come to expect that more often than not the process will result in aggravation and dissatisfaction because:

  • Very often, the transfer is never accomplished, causing you to begin again
  • The hand-off results in you going to the back of the line in that next channel and/or having to spend a lot of time just pressing buttons to get to the next person
  • The hand over, once it occurs, is unintelligent. None of the information you provided previously is transferred, and you have to start your story and providing information all over again
  • There seems to be no accounting or appreciation for how much cumulative time you have spent across the channels. There is no built-in escalation; invariably you have to reach a boiling point where you demand other action
  • The first question you are asked at the start of the process is if you want to take a survey on your satisfaction once you have finished

    customer satisfaction

No doubt, a better omnichannel experience with less friction involves:

  • Marketing, Sales, and Customer Service employees that genuinely care about whether you are successfully moved into the next channel
  • Systems that transmit information already captured, so you don’t have to repeat it
  • Systems to track your total time engaged across channels in your current session, and then have rules that take that into account
  • People and systems that automatically document key events and transactions that transpired, so that there is a comprehensive corporate record
  • A variety of choices when being transferred, all that are relatively seamless
  • Survey & feedback options that reward you for taking your time, and are presented after the process is completed

For example, suppose you first enter a mobile website seeking information, encounter a chat option, then the person you are chatting with provides you with a link, you go to the link and while reading it find a phone number, you call the phone number, and finally the call center person refers you to a Facebook Fan Page. Sound unlikely? Not really.   I actually encountered this case with an airline.

Consider closely this customer journey, which involved 5 channels (mobile web, chat, self service web, call center, and social), and your reaction might be that I’m describing a service case, not marketing.   Actually, I contend that in most cases interactions with customers involve both. Moreover, when the consumer intent starts as a shopping process, consumers predominately use more than 2 channels during their journey.

Practically anytime a customer engages, you should think of it as a service and marketing interaction.   Marketing, by definition, is the process by which you promote, sell, and distribute your products and services – and information on them. Using this description, nearly any interaction has the potential to involve some form of promotion.   But in the end, as Ben Franklin once said, “Well done is better than well said.”

Let’s go back to the case. I might have rated this encounter smooth and near seamless if the people, systems and processes were more geared and tuned to meet my requirements – the least amount of time and effort, with the result being what I started off seeking.   Although in this case my expectations weren’t met, it made for a great use case for the framework involved, and for the goals to aspire to.

Why is this seamless experience important?   The network effect

network effect marketing

Since I invoked a historical figure to quote from above, why not do it again.   “Quality in a service or product is not what you put into it. It is what the client or customer gets out of it.” – Peter Drucker.

I argue the same is true of marketing. It doesn’t matter how good you think your marketing is, what matters is what your customers or prospects think, and what they get out of it.

A credit card company I did consulting with for ages marketed their credit cards to me for 8 years using traditional physical channels.   I never converted.   Certainly all the marketing had an impact on my awareness of their products and brand, yet the exceptional omnichannel experience that I later had when I signed up for an entirely different service is what I now equate to their marketing abilities.

Of late, customer’s purchase decisions are influenced by online positive or negative reviews.  In a recent survey, 88% of respondents said they are influenced by online reviews when making a buying decision[i] So whether it’s the functioning of a product, it accessories and training, its price, the promotions on it, or where and when its available – all these aspects get reviewed and become your positive or negative marketing.   If the customer experience is a smooth one as they research, discover, and learn across channels – then you stand to benefit.

What systems are required to achieve a seamless channel experience?

Above all, you need a system that records and makes accessible all channel activities to all that may have to answer questions from customers.   Ideally, this system is integrated, with a unified front-end, so that customer facing employees don’t have to switch systems, toggle screens, and struggle to find historical records.

In addition, the channel systems that gather customer data should be able to:

  • Send data across channels so it can be prepopulated and used in the next channel – namely data like account number, order number, specific product inquiry, and reason for call
  • Trigger another system to update it or take prescribed actions, such as calculating elapsed time or sending an SMS or email

Comments and alternative views are always welcomed

Note:  These views are my own, and not that of my employer

[i] Dimensional Research – Customer Service and Business Results; April 2013

True Omnichannel Marketing – Part 3

In Part 1, I explored how and why to test for the right mix of channels.   In Part 2, I covered channel activity coordination and consistency.   In this post, I delve into using technology to achieve effective channel integration for optimal marketing decision making.

channel_integration

What is effective channel integration?

Channel integration is really all about intelligent data sharing for just-in-time decision making in the appropriate channel.   Marketing across channels in a way that is advantageous to both you and your customers involves efficiently sharing descriptive attributes about them that can be leveraged to make the best recommendations and personalized experiences when they are in channel, or when you are proactively communicating with them.

To illustrate, think about what you expect a business to be able to do when you go to their website.   Should they know your location? Should they be attentive to how you arrived at the site? Should they be aware of your recent purchases or activity in another channel?   What if today you achieved a new tier of loyalty?   I think we would all say that not only should they know these things (assuming proper permissions are given), but they should take them into account in the actions they decide to take in this channel interaction.

Yet too often, firms are not effective with getting the right data to the systems charged with calculating the next best actions for the channel in question.   Why is this?   From what I’ve observed, it boils down to these reasons:

  • Channel ownership in terms of data and decision rule making is still done in silos.
  • Channel owners are not given incentives to make changes for the greater good, but instead have measurements in place that encourage channel myopia. Without executive leadership for change, status quo remains.
  • If the time to get the right data and make a decision based on it is deemed to take too long, the tradeoffs to make this work are quickly dismissed as too costly or risky.
  • The analytical science, methodology and process involved to get to the right set of customer attributes for a given channel are not well understood, and there isn’t enough priority placed on solving for this.
  • The candidate pool of potentially predictive data that should be tested is not readily available, and the process to make it accessible and distill it down appears to involve too much effort, time and cost.

Why is channel integration important?

Without effective channel coordination and integration, as a business you will make less relevant and timely marketing actions, and risk failing behind your competition resulting in less satisfied customers, lost customers, and declining market share.

Evidence suggests that customers expect companies to understand them, at least in terms of being aware of past interactions and information voluntarily surrendered[i].   Moreover, they are increasingly cross-channel shoppers, using more than one channel in their buying process. If consumers sense firms “don’t have a clue”, it’s not uncommon for them to feel it’s their social responsibility to broadcast digitally via reviews, social media, or blog posts.   This can have an adverse impact on a company’s brand image. Think of it as a negative promoter score – or “net demoter score” that firms should aspire to improve.

Conversely, consumers often react favorably to activities and promotions that are relevant to them, and in the short run will reward firms with higher response rates (it’s not uncommon to achieve 3x or higher), yet more importantly long-term loyalty improves because of increased levels of trust, convenience, and meeting requirements, leading to higher lifetime value and more referrals.

Consider the dilemma businesses face today and then ask if better channel integration as described helps crack this. More than ever, consumers are impatient on two sometimes opposing fronts – they expect the right answer and they expect it fast.

  • It’s been said that today speed trumps quality, but actually consumers expect both, and if they don’t get both from you, they will shop around – and consumer switching, especially for younger segments, is on the rise[ii]
  • What does it mean to be making decisions in real-time – e.g., providing speedy answers? I submit that what is most important is providing decisions in the right amount of time to meet true customer expectations and needs.   So if a customer is clearly seeking deeper content on a particular product, offering them alternative product recommendations in sub-seconds may be less useful to them (and to their likelihood to buy anything from you) versus providing them detailed content on that product minutes or even hours later.   This is what is meant by JIT (Just in Time) decision making.

What systems are required to achieve effective channel integration?

Channel integration as described entails a number of systematic capabilities such as:

  • Maintaining a universally accessible channel preference center or data store that houses:
    • Consumer stated preferences
    • Channel effectiveness indicators organized by events and actions. For instance, if a consumer states a preference for direct mail yet data suggests they respond better to new product offers in emails, preserve and share that
    • Channel effectiveness indicators organized by timing.   Again, if its known that certain consumers have higher click thru rates on emails sent on Wednesdays between 11:30a and 1pm eastern time, codify it
  • Fast access to customer behavior and demographic attributes that can be fed to a given channel decision engine
  • Fast access to model scores and the ability to request recalculations as necessary for an interaction in a given channel
  • Fast access to personalized content and promotions that can be suitably combined with a prescribed channel action
  • Ability for one channel system to trigger transactional actions on another channel, such as when a customer is on a website, and the next best action is to send a personalized SMS
  • Facility to orchestrate a series of prescribed actions across channels that are set into motion by a genesis event or action on a given channel. The resulting flow diagram enabled by such a system might look something like this (there are many such systems in the market today):

 

flow

Comments and alternative views are always welcomed.

[i] My Buys – 6th Annual Personalization Consumer Survey; January 2014

[ii] National Consumer Agency – Market Research Findings: Consumer Switching Behaviour; September 2013

 

True Omnichannel Marketing – Part 2

In Part 1, I explored how and why to test for the right mix of channels.   In this entry, I explore coordination of channel activity

What should you coordinate?

Today more than ever, consumers have extremely high expectations regarding how they engage with businesses via the multitude of channels available.   The new engagement model both sets the bar high and includes higher risks and potential returns.   If vocal consumers sense a company “doesn’t get it”, for whatever reasons, they often spend extra time and energy letting others know about it (usually via social media and reviews), and conversely, if impressed they may spread the word.

Coordinating channel activity can simply mean doing a variety of things consistently across channels such as:

  • Offering and honoring the same prices and promotions across channels
  • Ensuring all of your staff across channels have access to all the consumer’s channel activity
  • Maintaining a consistent branding, style, and content delivery amongst channel actions
  • Always presenting various channel options at each touch point for ultimate convenience
  • Honoring consumer channel preferences

Why coordinate?

Answering this question strikes me as another case of common sense that makes great business sense, but isn’t necessarily that common.   How often have you been in a store and asked if they will honor the online price and received a strange and hesitant look?   Who hasn’t found situations where you have sent and email, or called a call center and transacted with a business, only to find there is apparently no record of this activity?

So the answer becomes rhetorical.   Who wouldn’t want consumers that are extremely satisfied because the business is ultra coordinated and consistent in everything they say and do, no matter the channel?   This experience invariably leads to positive word of mouth advertising, positive reviews, and positive publicity – resulting in more referrals, better loyalty, and more business.

How do your customers see your business?

Here is the key thought of this post and something that may help you soul search on whether the omnichannel experience you are delivering is indeed exceptional across a variety of consumer opinions:

Does each different customer who you deem as important to your future strategy experience your brand in a way that thrills them?

Invariably, this question entails a number of key areas for your marketing strategy. Namely ensuring you have a well defined audience & segment targeting and value assessment approach, and also taking steps to check, in a humbling, objective and outside in way, how you are coming across to your customers.

Consider these strategies to get objective feedback that can help you improve your cross channel consistency:

  • Read a sampling of reviews on different channels (e.g., website reviews, Facebook fan page).   Use a sampling strategy to ensure you are getting a good cross section of opinions. For example, if you have a 5 star approach, read a sample of reviews with ratings in each. Also, be sure to sample across time, so if you have reviews that span one year, sample some from each month or quarter.
  • Remember that there is inherently a bias in the sample coming from people who post reviews, so although it’s critical to consider these (since they are out there and thus perception is reality), also consider a strategy to survey others that may never post reviews. For example, consider a bounce back survey where the consumer responds with their feedback confidentially, and receives a small compensation for doing so (e.g., some loyalty points).
  • Research for views and publicity that may not be reaching your properties directly, but may have a significant positive or negative impact on how your brand is perceived. For instance, influencers in your market may be blogging, posting or tweeting about the experience they had with your brand, and considering that could be critical.
  • Angle for a way to also ferret out what (hopefully there is something) you are doing right. Why? Because otherwise you may inadvertently de-emphasize this thinking it wasn’t important, when it was yet no one bothered to tell you that.   Perhaps you are doing a fantastic job documenting your customer interactions in a timely and comprehensive fashion, still no one rewards you with stellar feedback on this.   Yet if you let this practice slip, you may well hear about it, after damage is done.

OK sounds smart – but this sounds hard also?

Maybe in large complex organizations getting much of this right isn’t easy, however often fairly simple practices and incentives work well.

An ordinary call center today has reps asking how they did, or offering a short survey when the call ends, but instead consider the following question, and what it implies:

“What is the single most important thing we (as a company) could do to improve?”

This question has many great aspects packed inside.   It gives the customer the latitude to consider their experiences and opinions not only for this interaction, but for any one in any channel at any time. It also isn’t limiting them to service or marketing interactions, as maybe they have an idea to improve your product.   Additionally, it forces prioritization, asking for advice on their most important concern.

Do I need applications, systems and technology for this?

The short answer is yes you do, and especially if you are a large enterprise.   However, yet again, these systems don’t always need to be extremely sophisticated.   Having simple call logs that are sharable may be all that is required, yet providing the right incentives to guarantee every representative keeps track of all interactions is the key.

Once more, if you are trying to track and analyze feedback, employing a system that can help sample and synthesize sentiment is certainly helpful, however doing this in a more manual fashion versus not doing it all is the wise choice.

Comments and alternative views are always welcomed.

True Omnichannel Marketing – Part 1

What is good omnichannel marketing?

Having been around enough to see this idea evolve, I have a certain view on omnichannel that isn’t always in vogue, but to me speaks to the essence of good marketing.   That is, that good omnichannel marketing is testing the right mix of channels for your business (not what others are doing) that represents the optimal mix for your customer’s engagement with you at a given point in time.

Let’s dissect this thought by concentrating on some key words and why I believe things may not be in vogue but represent best practices.   First, inspect the choice of the words, “your business”.   The mistake I see made by so many marketers is they flock like lemmings to the newest marketing trends, while abandoning old ones.   There is nothing wrong (and in fact it should be in your marketing fabric) with testing new ideas, but the second key word used is “testing”. So putting these thoughts together, focus on what works for you and your customers, challenge those champion channels with new ones, yet keep the right mix that returns that best current results. Always observe what your competitors and fellow practitioners are doing, however intelligently form hypothesis and then systematically test them.

Next, consider the choice of the words, “optimal mix”. How do you determine what is really optimal?   This gets into an area I’ve explored in depth for many years known as attribution.   The mistake I see many marketers making is they either choose to ignore this, saying it’s too hard, or they work it in only one area, for instance for their digital spend or separately for their general advertizing budget.   As marketers, we have to let all of our efforts compete on an equal playing field. None should be considered untouchable, nor should any be chucked into the rubbish bin because they feel old school. The reason they think it’s too hard is more about organizational challenges then technological or optimization techniques available. I’ll always remember a quote from an enterprise retail marketing executive on this, saying “changing the way we decide on marketing mix is like starting a jihad.”

Why you should fight the good fight

Although it may be daunting to some, this shouldn’t stop you from pursuing true omnichannel optimization. If you do this better than your competition, you will be more likely to succeed now and in the future.   You don’t necessarily need to use overly complicated algorithms, techniques, or systems to accomplish a more optimal mix of marketing spend across your channels. You simply need to be able to measure the effectiveness of programs executed in each, and then ensure they are fairly competing for current and future marketing budget.

Now ponder the term, “your customer’s engagement.” It’s not about what you think is best, it’s about which channels which customers want to use to engage with your business.   I picked the vital words which channels for which customers because you can’t use a one set of channels fits all segments of customers.   For example, if you have a significant older demographic segment, they may well like to engage with you by phone or even by mail. Yes mail, this thing that the post person still delivers to mail boxes every day.   Be objective with your analysis of channels effectiveness and not just trendy. Also, don’t be afraid to use fairly basic measurement techniques if needed to simplify the problem, such as first touch or last touch, or equal weight / credit, but use these differently by channel. So for example, last touch may be very effective with certain digital media, however first touch may be more appropriate for certain traditional channels, or for certain types of marketing efforts, such as lead generation.

If there is one thing that is certain, its “Change Happens”

Finally, let’s mull over the phrase, “at a given point in time”.   I included this because what I’ve seen is that marketers do something, feel confident in the answer, and then don’t challenge it often enough. For instance, perhaps you did some valuable work that shows your best mix of channels & budget for your elder demographic segment is 50% mail, 30% phone, 20% email, and 10% other. That’s great, for now. But in just one year this segment’s age has changed materially, and perhaps their preferences and behavior & habits.

So be objective, be humble, be inquisitive, and test everything.

Note:  These views are my own, and not that of my employer