Why Do I Need a Customer Journey Map?

Customer journey mapping helps you visualize your customers’ experiences from their point of view across all the points of interactions during their experience with your brand.  Clarity into the customer journey and the specific moments-of-truth that occur during any engagement with your brand, can lead to improved customer satisfaction, higher value exchange and long-term stickiness.  I think you’d agree that these are pretty good goals!

We aren’t talking Nirvana here but let’s just acknowledge that we all return to the brands that make the experience “feel good!”  Many company’s use Voice of the Customer (VoC) studies as proxies for customer “feelings”.  Although VoC studies can and do measure overall satisfaction or its lack the results are generally aggregate scores which can condense and obscure bi-modal issues at certain touchpoints that affect the desired experience that the brand is trying to engender.  Customer journey mapping exposes those critical touchpoints where frustrations might occur thus allowing you to diagnose the specific moments that matter, clearly indicating what needs fixing.

It’s not a stretch to say that if “feeling good” is the desired state, then hearing that “this experience sucks!” is definitely a problem for brands and typically manifests in lower total customer value, smaller basket sizes or rampant attrition and churn.

So at a minimum there are at least three situations where customer journey mapping could help: flagging sales, decreased loyalty and an increase in attrition.  Note that there are other reasons to use customer journey maps (CJM) such as new product commercialization or introduction or the rejuvenation of a product or service.

Let’s look at decreased loyalty as a problem that might be diagnosed through a CJM.   For years the cable & broadband industry expected attrition and knowingly compensated for it by continuous acquisition.  Loyalty was an anomaly, prized but unexpected.  Customer satisfaction (VoC) was measured regularly and it was assumed that mid to high customer satisfaction ensured subscriber loyalty.  Analysis often showed no correlation between the two, in fact, it wasn’t unusual to find mid to high customer satisfaction scores among premium customers who then attrited.

The problem was that customer satisfaction studies were too generic, as I mentioned earlier, lumping all facets of customer service into a single question or two.  In reality there were many sides to customer service and one of the major drivers of dissatisfaction – installation scheduling – which usually was rated quite low -was lumped in with other drivers like representative knowledge or ability to answer all the questions – which was usually rated highly.  The result was a medium and sometimes high level of customer satisfaction which provided no true measure of attrition and in fact skewed the attrition model when it was added as a component.

A customer journey map detailing a new installation or upgrade, for example, would undoubtedly have pinpointed some of the most egregious cable service frustrations:  long wait times for installation and large service windows and/or unpredictable technician arrivals.  It might have also shown that the high scores given, on average, for rep knowledge or comprehensiveness of answers might be frustration points when “knowledge” elements were broken apart.  And the ability to question and map the feelings around the events would further indicate where those moments-of-truth lie and which would have impacted loyalty.

In general, the Customer Journey Mapping process is oriented towards problem identification and resolution and usually results in several distinct outcomes.  For example, you will:

  • Gain a comprehensive look at the customers’ journeys across all your touchpoints
  • Identify the key pain points and “make or break” moments that affect use/ purchase/repurchase
  • Understand the “why” behind behavioral analytics
  • Identify and prioritize opportunities to get to the “feel good” customer experience more often
  • Communicate and align the organization around a customer-centric model
  • Model change management and set priorities

In summary, mostly CJMs are a guidebook towards becoming customer centric.  They function as a compact visual representation of the customers experience with your brand – at a particular point on time.  Used correctly and overlaid against your own perceptions, they are a good first step in taking corrective action about your flagging sales, loyalty deficits and customer attrition.

I’d like to know what you think!  Leave a comment if you like

First, Map the Customer Journey

New research suggests that marketers should organize around a single, best understanding of the customer and her journey to drive personalized customer experiences across platforms and at scale.

In response, most marketing automation software vendors today are building customer journey functionality to support these types of personalized experiences.  However, smart marketers know that you can’t proscribe a customer journey…software can’t tell you how the customer feels about interacting with your brand or what attitudes she holds and how that affects decision making.  Neither software functionality alone nor machine intelligence algorithms can account for what is really meaningful to the customer – their story in their own words!  This post will take a brief look at the process of journey mapping and why it matters.

If you want to improve engagements with your customers, you need to first understand their goals, challenges, aspirations, expectations, attitudes, feelings, wants and needs enacted out over time across multiple stages and touchpoints as they engage with your brand.   There are a number of process steps that should be taken to map the journey (to be discussed in future posts.)  Generally, the best first step is to literally talk to them – via focus groups, brainstorming, and individual interviews – and to draw in the internal stakeholders to react and interact to the customer input.

When I speak with executives about customer journey mapping I hear interest and excitement around the process but a misunderstanding about the purpose.  Customer journey mapping is not entirely about how a customer reacts to the products, services and communications you serve up to them.  Rather it’s about understanding their decision processes and influences and then leveraging what you learn to make the engagement more rewarding and your investments more profitable.

Here’s a story to illustrate the power of direct customer input.

 A large manufacturer of medical equipment had recently upgraded its MRI machine to increase patient comfort, image consistency and professional satisfaction of the professional staff.  What they didn’t know was how to introduce the equipment to audiences that might find the equipment intimidating.  So they chose to map the patient experience. 

The process began with focusing on a specific patient persona and conducting interviews to capture reactions and behaviors associated with a diagnosis event. Functional and emotional needs were recorded throughout the process with an eye to isolating any specific moments that impacted the patient’s primary goal: to feel safe while having an MRI.

These were the moments that mattered – the company used them to re-design an experience that created a fun, engaging environment for the MRI patient.

Many experts agree that by understanding the “as is” state of the customer experience today, you can predict the “to be” or future behavior. As Siddharth Gaikwad, at Dell Digital says “by overlaying possibilities [what the company wants to sell] upon customer journey maps, organizations are able to better visualize which aspects of their business they should focus on…”

Customer Journey Mapping helps companies to understand the broader context of its relationships with customers but it is a means to an end rather than the end goal itself.  It’s just the beginning of closer engagement.

Ultimately, wouldn’t you rather create a differentiated experience that delivers on the brand promise vs. the tried and true journey based on what you perceive to be well-known pain points or stakeholder needs?

Lets start speaking about your customers’ journeys today!  email me at ann@dbmcatalyst.com.

 

Why Personalization Matters

Companies are facing a challenging time today wrestling with the requirement to personalize communications and offers.  What’s more, personalization is about much more than segmentation, it’s about calibrating offers to a level of detail only achieved by understanding the consumer’s mindset and behavior at the point in time when interacting with your brand. Three articles from MarketingProfs.com discuss personalization from the challenge of accomplishing real time personalization to how to implement radical personalization and the challenges of personalization in digital marketing. Enjoy! Marketers Struggling With Real-Time Personalization Understanding the Five Pillars of Radical Personalization Marketers’ Biggest Obstacles to Effective Personalization   Tell Me What You Think! DBMCatalyst

Real-time Customer Segmentation

I’ve been around long enough to have heard the term “real-time” associated with a variety of marketing technologies, how about you?  And I often wonder about the value of that type of immediacy let alone the possibility of actually interacting in real time with my customers.  It’s always been one of those marketing aspirations which seems never quite actualized.  Or at best, it’s realized in a very mechanical way, such as re-directing a consumer to a new offer branch in a campaign based on their real-time response in a campaign.  All of which is better by far than the “blast” form of email or direct mail – which is still practiced in many industries.

In my opinion, the only value in “real-time” is knowing who your customer is in that moment as they interact with your brand.  And by “who” I really mean not only their demographics or psychographics but also their past behaviors and transactions all of which tell me something about their capacity and propensity to buy as well as their interest in/affinity towards my product.  When properly modeled the result is a score that  effectively segments your customer according to their lifetime value to your brand which enables you to deliver the most personalized, effective offer at the most profitable price.  This is real-time segmentation.

There are numerous approaches to segmentation from the simple demographic/psychographic classifications to sub-segmentations which employ sophisticated modeling techniques like factor and cluster analysis.   Ultimately most segmentation models give you a piece of the picture but even when they come close to the full definition of “who” the customer is, the result is in the “rear-view.”  The learnings  are applied after the fact, in a sense they describe who your customer “was.”   The moment of connection with your customer is lost or delayed.  The most sophisticated companies will rigorously update their customer segmentation models, but again, they are not describing the customer in “real-time” purchasing mode.

Real-time segmentation and scoring is possible today and will soon be enhancing the customer experience in not only call centers and online, but also in social and mobile channels.

Ask me about how!

Ann McCartan, DBMCatalyst

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Mini-Segmentation, what can you do?

We’ve spoken about the practice of aggregating like customers into groups or segments to better target and market to them.  And how to utilize modeling – factor and clusters – to distinguish individual characteristics within the segment they are assigned to.  These are complex segmentations built with a lot of data on each customer.

Another approach is more organic and allows the marketer to build segmentation profiles a step at a time as more data is obtained.  The good news is that content and messaging can be created at each step based on specific information gathered.  The goal is an upward journey to 1 – 1 personalization and a true 2-way conversation but these mini-segments make effective communications possible.

You don’t have to build the whole segmentation before marketing effectively to your customers.

Tell Me What You Think!

Ann McCartan, DBMCatalyst

 

B2B Segmentation – the impact of behavior

Just a few more thoughts about segmentation…B2B segmentation specifically.  Segmenting B2B customers is both simple and more complex at the same time.  Simple because of smaller datasets and widely conforming variables, but more complex because of a greater number of disparate data sources – and aligning data definitions for each – and because of the very real problem of defining the “customer.”  Mostly I’ve seen companies overcome the above complexities in all but one regard – properly parsing and modeling customer behavior.

What does that mean?  consider this:  how often and how easily are customer tenure, i.e., length of time as a customer; specific product or service usage – i.e., name, SKU, quantity; and customer recency, i.e., last purchase date/ship date,  tracked and added to a customer or analytics database?  How many years of data are combined and stored in such a database:  1 year? 3 years? 5 years?  Modeled correctly, these few variables will provide actionable insight into your B2B customers’ behavior and when added to their firmographics profiles will impact the relevancy of communications, offers, promotions and service-calls.

Most of the B2B segmentation I’ve seen is based on a combination of firmographics and revenue, some even based on year-over-year revenue or 3 years of revenue.  Or sometimes the segmentation is based on product profiling.  But rarely are they enriched with behavioral data such as defined above.  Why care?  because this means that the company will forever be stuck knowing what their customers “did” but not what the customer will “do next.”

Wasn’t it Wayne Gretsky that said “I skate to where the puck will be not where it has been.”

Properly combined with customer firmographics and modeled for predictive outcomes B2B customer behavior will have a powerful impact on future growth.

Tell Me What You Think!

Ann McCartan, DBMCatalyst

 

 

 

Sub-segmentation – the power of relevancy

I recently read a research paper “Customization with cross-basis sub-segmentation”  which got me thinking about the real power of sub-segmentation.  And I’m betting that while segmentation is a common tool used by marketers, sub-segmentation isn’t widely understood or used.   Do read this article.  It’s an older article and a bit dense but the advice is timeless.

I’ve been involved with many companies who routinely group customers by homogeneous variables such as spend, profit, geography, trade-area, industry, product purchases or whatever variables are key to their business.  All good and prerequisite to effective offer targeting, but ultimately descriptive, i.e., who they are, what they have purchased but not how they act in the future.  Through various types of modeling customers can be scored as more or less responsive in different marketing channels – either to click or call or visit a store and/or to buy what you are selling.  But that only tells you WHO to market to.  I have to say that I, too, believed at one time that knowing WHO was enough.

The interesting piece, and, yes, I know, not new news, is raising the bar through offer customization.  Customization enables relevance.  Simple.  But what I want to discuss here is the effective customization generated by a process known as sub-segmentation.  And further that it’s quite likely that sub-segments even within one group (segment) can often act differently, display different buying behavior and responded differently to offers that you believe are germane to the whole group.    Through sub-segmentation it is possible to tie previous purchase behavior so closely to each customer that it becomes virtually predictive and definitely more relevant.  And, that’s WHAT to say.

Let’s look at two sub-segmentations, RFM (recency, frequency, monetary) and the development of interest scales.  RFM is a well-known, often utilized method of segmenting customers based on purchase recency – how long since their last purchase; frequency – the number of previous purchases; and monetary – the total amount spent by the customer in any timeframe but often either over their tenure or over the last twelve months.   Once customers are sub-segmented by this method a customer contact strategy becomes apparent, e.g., best customer (retention and loyalty), growth customer (upsell), and maintenance (recent buyer, new customer.)  But again, all best customers or new customers are not equally likely to respond to one offer message even when targeted to their segment.  RFM offers little relevance.

The development of interest scales requires more sophisticated modeling.  It typically involves measurement of how often the customer buys various product categories, the ranking of each customers’ interests into a scale and uses this analysis to create sub-segments.  So the frequent shopper of books online – who also slots into a single segment based on the types of characteristics above – proves to be not just a book lover but a devotee of Science books based his interest scale.  He may also buy other book categories, but buys Science considerably more often.  It is also likely that the Science category far outstrips all other categories.

Of course the development of the interest scale isn’t so simple and requires sophisticated analytic tools like factor analysis which enables the identification of the purchased products and cluster analysis which is used to group products in such a way that products in an assigned category are more similar to each other than to those in other categories, thus reducing the overall product set.  And, of course, scoring customers accordingly.

By combining the two sub-segmentation approaches, you become able to communicate more relevant offers, speak more knowledgeably to your customer about things he in interested in and convert more sales in the process.

Let Me Know What You Think!

Ann McCartan, DBMCatalyst

Segmentation, a Deeper Look

Recently I posted a brief, basic explanation of Segmentation.  I mentioned some of the most common applications for segmenting customers for marketing purposes.  Clearly the more narrowly customers are grouped by commonalities, the more able the Marketer is to direct content and offers to meet their particular interests or behaviors.  It’s basic targeting, yes?  and the ideal outcome is always greater incremental revenue, profits and the sense by the customer that the company understands them and is providing relevant messages.   As a first step, I always look to customer characteristics and behaviors as prerequisite to defining segments.

As a second step in the process, before a customer segment is acted upon it should meet several other business-focused criteria.

  • It is possible to measure.
  • It must be large enough to earn profit.
  • It must be stable enough that it does not vanish after some time.
  • It is possible to reach potential customers via the organization’s promotion and distribution channel.
  • It is internally homogeneous (potential customers in the same segment prefer the same product qualities).
  • It is externally heterogeneous, that is, potential customers from different segments have different quality preferences.
  • It responds consistently to a given market stimulus.
  • It can be reached by market intervention in a cost-effective manner.
  • It is useful in deciding on the marketing mix.

If the business can identify distinguishable customer differences and commonalities which can be can justified from a marketing and financial perspective then solid customer segments can be derived.

Tell Me What You Think!

Ann McCartan, DBMCatalyst

 

 

Who Owns the Sale?

Who hasn’t been in the middle of the great “controversy” about whether Marketing or Sales owns a sale which arises as a result of a marketing campaign?  Moreover, how much of the sale can be attributed to each sales or marketing channel?  And don’t even bring up which inbound/outbound channel tipped in the sale…..

I recently read an article “Defendable Multichannel Sales Attribution“, written by Tom Reid at the Hacker Group, which deftly explains the core issues.  I mostly agree with his points, more on that in a bit, and it’s worth the read.  Particularly so because he stresses the necessity of good data, test & control and the establishment of business rules for channel attribution.

I won’t kid you, it’s hard to pull off multichannel attribution primarily because success hinges on the integration of competing departmental/units under pressure to achieve their own KPIs.  Hey, the technology (database) is easy comparatively. To summarize, he asserts that there are three approaches to sales attribution:

  • Rules-based: credit (the sale) is attributed to whomever drives the last touch (sometimes the first)
  • Contribution: all participating channels receive mention and even a weighting of their contribution and/or a proportion of the sale
  • Statistical modeling:  this isn’t detailed but could lean towards multivariate testing of several types which look to identify the relative impact of channel, content, timing, frequency, etc. of each of the overall campaign components

While I don’t strictly agree that statistical modeling is always necessary, Reid lays out the necessary data and design components needed as input.  Those inputs alone will enable quite satisfactory, rich analytics which will allow you to assess your current campaign, attribute proper channel impacts and to trend or predict future success.

In my opinion both Marketing and Sales own (any given) the “Sale”  but each must be given proper defensible attribution.

Let Me Know What You Think!

Ann McCartan, DBMCatalyst.com

Marketing Automation

Automating the marketing processes and tasks that are a routine part of your in/out bound marketing and selecting the right hardware/software will cut costs significantly and positively impact effectiveness.  Where are you in the process?

  • Is this the first time you are automating your marketing processes and tasks? the first time you are purchasing an email platform, database or analytics and campaign management software?
  • Or are you already automated and simply need to upgrade your solution or add a key program?

Wherever you are headed, you will need a roadmap!  Do you need:

Marketing Automation – Vendor Review

Marketing Technology Implementation

Once your goals and objectives are mapped to the right solution underpinned with to a coherent marketing automation strategy and an achievable Roadmap, your marketing automation business case will flow.

Contact Me at 339-227-7591 or ann@dbmcatalyst.com