Segments, Personalization

But enough to make a difference in their buying behavior?

People don’t like being lumped into marketing segments in Retailwire
by Guest contributor  includes expert discussions at link

MarketingCharts staff  

Through a special arrangement, presented here for discussion is a summary of articles from MarketingCharts, which provides up-to-the-minute data and research to marketers.

Personalization is all the rage these days, with a primary goal being to enable one-to-one communication. A new survey from Selligent Marketing Cloud may provide one reason why marketers who have yet to move to individualized campaigns may want to work on those efforts rather than marketing to broader segments.

The survey, fielded among 7,000 respondents globally, found an overwhelming preference for being treated as an individual rather than a member of a segment. Fully three-quarters (74 percent) agreed that they expect companies to treat them as an individual, not as a member of some segment like “Millennials” or “suburban mothers.” The figure was slightly higher (77 percent) when it came to U.S. respondents. ...   "

Spectral Clustering and Decision Process Improvement

Good, detailed piece in DSC on motivation for Spectral Clustering.  Not a method we used in the enterprise, never getting beyond K means and forest methods, but the case is made that better clustering methods can get you closer to the actual decision process. Getting closer to selectively using specific data resources to match and improve existing decision processes is valuable.

Thus the link to decision tree oriented methods.  Also related to segmentation methods driven by clustering.   Finally,  mentioned in the article, how this can be used to  the specific value of particular data assets. That was an area we looked at closely.  Will examine possibilities.  Ideas?

Remembering Photos with Deep Learning

In CACM:  Deep learning photo memorability

" ... Researchers at the Massachusetts Institute of Technology's Computer Science and Artificial Intelligence Laboratory (CSAIL) say they have developed an algorithm that can predict how memorable or forgettable a given image is almost as accurately as humans.

The MemNet algorithm builds on previous work by CSAIL researchers to develop a similar algorithm for facial memorability. The researchers fed the algorithm, running on a deep-learning network, tens of thousands of images from several different datasets that had been given a "memorability score" by human subjects. When they pitted MemNet against human subjects by asking both to predict how memorable people would find a never-before-seen image, the algorithm performed 30% better than existing algorithms and within a few percentage points of the average human performance.   ... " 

China Customer Data Opens Potential

Remember looking for just this kind of detail data just a few years ago to model the Chinese Consumer in more detail. Quite a potential here.  This is big enough and detailed enough to drive some real value.

Chinese Internet Giant Tencent Opens Its Trove of Data to Agencies
Dentsu Aegis Network and GroupM Are the First Partners ... 

Chinese internet giant Tencent is massive in scope and in the variety of ways it reaches users. Its mobile social platform WeChat has about 650 million monthly-active user accounts; another platform, QQ, has 860 million. It's big in games, music, video and news. And it has the data that goes with all that. ...  " 

Strap Startup for Marketing Analytics

Brought to my attention via the Brandery.  Strap.      Also, their Brandery information.

" .... Strap enables actionable human data to inform and improve marketing and engagement programs. We believe the consumer centered journey must be personalized because a more personal world is a better world. Through powerful analytics and segmentation from smartphones, wearables and health data applications, Strap empowers some of the world’s largest brands and retailers to securely engage consumers at the right time while building brand loyalty and gaining valuable consumer insights. Strap was founded in early 2014 by Steve Caldwell, Patrick Henshaw, and Joey Brennan, and is headquartered in Cincinnati, Ohio. Follow Strap on Twitter at @getstrap. ... " 

Generation Z is Coming

I am not a fan of generational labels.  I have seen too much variance within them to trust them much. But still, you have to know the definitions to follow what is said about this large scale age-based segmentation.  Quite an extensive survey.

 Useful piece in Knowledge@Wharton:

Millennials on Steroids’: Is Your Brand Ready for Generation Z?   It’s still early days for Gen Z — its oldest members are still in their teens or early 20s — but marketers are trying to get a handle on what they want and expect from brands. ... 

And now here comes Generation Z, the post-millennials loosely defined as those born between the mid- to late-1990s and 2010. Gen Z, which represents about a quarter of the U.S. population, is coming of age in the Era of Instagram; coming of age post-the Great Recession, and coming of age when an African American president and multiple women running for the title is a political reality. (This group hasn’t been the source of any generational angst yet, but give it time.)   ... " 

Cracking the Digital Shopper Genome

In McKinsey:  Thoughtful piece.  The genome template idea is a good place to start thinking about understanding some segmentation or knowledge understanding.   Maybe not as good as a complete ontology.  " .... Cracking the digital-shopper genome ... Companies have more data at their fingertips than ever, so why do online shoppers remain such a mystery? The solution begins with bringing all the information together to form a meaningful picture of the consumer. .... " 

Omni Channel Customers

Interesting new classification of customers.

In CustomerThink,
" .... If you found yourself checking a new piece of clothing at a store, while looking it up on the mobile app on your iPhone, only to purchase it later on the website and have it delivered at the store closest to your home, all the while sharing your experience on Instagram, you are a very desirable “Omni-Channel” customer.

Omni-channel is different from multi-channel. While multi-channel customers were merely able to purchase an item in-store, via mail-order catalogue or online; Omni-channel is defined as a customer-centric experience where different sales channels combine into one unique experience. Customers can decide which media they use to engage, and are free to cross over the different channels without “friction.” They are actively engaged and at the centre of interaction with the brand.   .... " 

Marketing Automation

In Silicon Angle by Maria Deutscher: " ... What you missed in Big Data; A new era for marketing automation ... Marketing made a comeback into the analytics discussion last week after Radius Intelligence Inc. raised a hefty $50 million from investors to support the development of its business-to-business targeting service. The funding caps off a record year that saw its revenue quadruple thanks to an influx of new clients drawn to the prospect of being able to better identify future opportunities.  ... "

Radius facilitates that with a segmentation engine that not only provides insight into different subsets of an organization’s existing customer base but also outside groups that might be interested in its offerings. The company claims that its automated approach has enabled some users to increase their sales severalfold through targeted expansion into new segments.   ...  "

Creating A Marketing Persona

Market equity in a persona, simplified.  " ... The foundation of marketing is the process of identifying, meeting, and satisfying customer wants and needs.  In order to meet their needs you must have a true understanding of your customers, their emotional triggers and what drives them. ... " 

Coke Consumer Clusters

Coca-Cola rewiring marketing around ‘consumer clusters’ to make sales pop

 The drinks maker’s chief executive Muhtar Kent let slip the strategic shift today (22 April) when he told analysts on a conference call that its focus on “customer clusters” had helped put sales on the road to recovery. Sales jumped 1.3 per cent to $10.7bn in the three months to March, propelled by a 6 per cent boost in North America, its biggest market. .... 

   .... Struck by the terminology,   'Consumer clusters' that I cannot define precisely .... Nor can the article .... Segmentation in the usual sense, I presume.

Science of Segmentation

The Science of Segmentation: What Questions Should You Be Asking Your Data? Attended this webinar.  Sponsored by Pivotal.  As the webinar suggests,  segmentation is an analytics need that most every company can use, and is an excellent place to start using Big Data methods. The Webinar talks technical details as well as technical process and results analysis.  Slides and recording.

February Analytics Mag Emphasis on Data Visualization

February 2015 Informs monthly on analytics, the leading professional organization for analytics practice.  The most practical and largely non technical periodical I receive on the topic. Examples, hints and value examples.  In this issue, on  sports, marketing and Example:

‘Clumpiness’ more profitable than traditional marketing segments
Marketing managers traditionally segment customers by three summary measures (also known as the RFM model): recency (the period of time since their last visit), frequency (how often they visit) and monetary value (how much they spend on a visit). However, a new study published in the INFORMS journal Marketing Science shows that, in contrast to traditional market segmentation, one based on “binge consumption” brings a higher long-term return to business. .... " 

Science and Art of Segmentation

A favorite topic.  Segmentation.  Classically a large amount of analytical effort in CPG  has been put into this topic. Is it science or art?   It is, both I agree.  But the specifics of this art and how it interacts with design or management decisions are often hard to describe.  Should it continue that way since we now have much more data?   What are the implications?

What Consumer Segments Say

Regrettably presented as an infographic, but an interesting view of consumer segmentation.  Points through to a white paper that requires registration.  " .... The white paper provides critical insights by exploring the attitudes of American consumers toward sweeteners and how those attitudes affect shopping behavior for specific products and brands.  ... "  ... What percentage of consumers say they "avoid or are consuming less soda" vs. the percentage that actually buy? Find out the answer to these and other questions that reveal the difference between what consumers say vs. what they do in this fascinating online infographic ... " 

Improving Customer Segmentation

And the further development  of customer segmenation.

" ... Customer Segmentation Moves into the Fast Lane   ...  It is a common marketing dilemma: Companies know that targeting their customers with greater personalization and timeliness will unlock value, yet customer segmentation strategies often fail to deliver the expected ROI.

The problem is that traditional approaches to customer segmentation are fraught with difficulties. ... "

Managing Customer Experience

An impressive writeup about how companies like McDonald's are attempting to manage customer experience.  Can it really be optimized, as they say, when people are involved?

" ... McDonald's customer experience management (CEM) is a good example of what companies can strive to achieve. SAS Customer Intelligence expert John Bala says McDonald's special sauce, so to speak, is that the customer experience is always at the center of its business, and the company keeps it there using an analytically-driven optimization process.... " 

" ... "Preference research, consisting of both qualitative and quantitative studies, can help organizations gain insights on customer shopping, pricing, product usage, and service support preferences," KPMG suggests.
"This critical first step is not about creating a new segmentation scheme." Instead, the focus needs to be on a number of of customer-centric variables, such as gaining insights regarding (1) how prospects hear about new products; (2) the factors that influence where they shop and for what; (3) onboarding needs and expectations when prospects turn into customers; (4) how customers and prospects like to get help when issues arise; and (5) the perceived value at specific price points, and how these relate to market trends and competitive offerings ... "

Marketing Engineering Revisited

I am reposting my review of this book below.  First because I had a need to take another look at it.  Second because it now has a second edition, which I have not looked at yet.  Love it as a mix of quant and qualitative methods.  ....  Wish I had the excel sheets that implement the methods described. 

As part of a practice of applied marketing meeting at Wharton I received a copy of the new book: Principles of Marketing Engineering, by Gary L. Lilien et al. Marketing engineering? Could there be such a thing? At least it's not marketing physics. First I admit though I have taken many engineering and physics courses I have never taken a marketing course. I have learned a bit of the quantitative aspects of the field over the years here.

I had a chance to read and overview a good portion of this book, and to my surprise it does a good job of positioning marketing as quantitative engineering in a meager 192 pages. Each topic: response models, market share, customer value, segmentation, perceptual maps, forecasting, conjoint, new product development, marketing mix and promotions are carefully positioned with only a minimum number of equations and some real-world examples.

Surprising, too is that this book is readable, I managed a third of it on a long flight. I don't think it can be complete given its size, but it positions a lot of fairly new techniques well. I would like to go through this book with a knowledgeable P&G person to see if, and how we use each technique, and have altered it to our own requirements. Much recommended for someone who wants a readable introduction to modern quantitative marketing methods. Even the analysis of Web 2.0 topics like blogs are mentioned, and the use of advanced simulation techniques to iteratively test proposed solutions.

The primary author Gary Lilien of Penn State, is one of the well-known deans of marketing science. He has a consultancy (who doesn't) called DecisonPro. They sell a number of marketing analysis frameworks that work in Excel, free for evaluation, have not tried any of them.

Wal-Mart Labs Buys Analytics

Have not heard much from WM labs of late, but these acquisitions are interesting.  " ... Walmart, via its Silicon Valley innovation lab @WalmartLabs, has made another acquisition today, continuing its shopping spree. The company is announcing that predictive intelligence startup Inkiru will be joining Walmart Labs to accelerate the retail giant’s analytics capabilities. Financial terms of the deal were not disclosed.  Inkiru’s platform is an active learning system that combines predictive intelligence, data abalytics and a decision engine to influence and determine customer interactions. Benefits to using Inkiru include being able to reduce fraud, improve customer segmentation and targeting, and more. .. " 

Gary Cokins on EPM Analytics

A piece that overviews some of Gary Cokin's view on analytics.  Have  read and passed a few of his columns.  Well done.  He talks about Enterprise Performance Management (EPM), not a term we used:  " ... Think of EPM as an umbrella concept. EPM integrates operational and financial information into a single decision support and planning framework. These methods include strategy mapping, balanced scorecards and dashboards, customer profitability analysis (using activity-based costing principles), forecasting, driver-based budgeting with rolling financial projections, and resource capacity requirements planning. Most of these methods have been in existence for decades, and many even before there were computers. What makes them relevant now is the need to integrate them for faster decisions to more complex problems and opportunities. The EPM methods in turn fuel other core solutions, such as customer relationship management, supply chain management, risk management, and human capital management systems, as well as lean management and the Six Sigma initiatives. It is quite a stew, but they all blend together. Embedding analytics of all flavors into EPM methods – such as correlation, clustering and segmentation analysis – enriches each of EPM’s many methods. .... "