Tag Archive for 'Predictive Analytics'

In the press: Marketing Via Invoices and Billing Statements

Published on June 30, 2010 in Leslie Nogue. 0 Comments Tags: , , , , .

Leslie Nogue, Pitney Bowes Business Insight

The July edition of Marketing AdVents features a byline authored by Pitney Bowes Business Insight’s Director of Strategy, Suresh Nair.  In the article, Suresh discusses the manner in which companies are beginning to use statements and invoices as a marketing vehicle.  By combining transactional information with targeted communications in transactional documents such as statements, invoices, and notifications, organizations are able to generate sales, reduce churn, and build customer loyalty.

Suresh argues that marketers need to own the bill, encouraging them to influce the content, format and customization of the white space typically found on statements and transactional documents.  He also outlines just how effective transactional document marketing can be, given the 95% open rate on these types of documents.  Read the full story…

On the Hunt for Unique Economic Indicators

Published on May 26, 2010 in Kyle Bingham. 0 Comments Tags: , , , , , .

Kyle Bingham, Pitney Bowes Business Insight

Economists look at a variety of sources for indications of economic recovery – sources like national statistics on unemployment filings and consumer confidence scores. Lately, local indicators have been catching my attention. I live in a small town of 4,000 in the state of Michigan, a state which has the highest state unemployment rate in the country. Since 2007, four homes on my street have gone into foreclosure, but in the last year, all four of those properties have been sold. Although the sale prices of those homes are significantly lower than their values 3 years ago, the sales themselves may signal that the overall supply of foreclosures is decreasing. But while some local indicators are signaling economic improvement, others are showing that the economy is still struggling.

Local indicators abound. Recently, I took my vehicle in to get fixed at my automotive repair shop. When I quizzed the repairmen about business, they said it couldn’t be better. In the recession, it seems people are holding onto their vehicles longer to avoid high car payments, which translates into more trips to the shop for repairs.

Here’s an odd economic indicator: according to my uncle, a hearse driver in the central Wisconsin town in which I grew up, business is down because more people are opting for cremation, a cheaper alternative to burial.

Time magazine had an article that highlighted some odd economic indicators, like the increase in hikers on the Appalachian Trail. An article in Kiplinger.com took another amusing spin on economic signals, with 10 unique indicators to watch during the recession. I had no idea that, in some areas, the increase in bug bites may be attributed to the recession! A recent article in The Wall Street Journal cited an economist in San Francisco who can gauge the local economy by examining passenger tallies from the transit system near the Union Square shopping district.

Obviously, it is more relatable to talk about indicators at the local level, but what is interesting is that we don’t hear about these so-called indicators when the economy is doing well. Maybe in good economic times, people are too busy making money to notice. While it is fun to debate the local economic drivers, it is also important to follow the traditional market indicators. Pitney Bowes Business Insight has developed its own product, called MarketPulse, which correlates economic indicators with market-by-market sales performance of retailers and other operators.

What indicators are you seeing as both positive and negative? traditional in nature and more unique? Is your barber cutting more haircuts? Are there more moving vans at the local truck rental (more people moving into town than leaving)? How are sales at the local gift shop? Did your Girl Scout troop sell more or fewer cookies this year? Are parking tickets up or down in your town? Hopefully, all the signs point to an economy in recovery. Whether they get back to pre-recession levels, though, is fodder for another blog post.

Retail 2.0: Brick vs. Click

Published on April 1, 2010 in Eric Steckling. 0 Comments Tags: , , , , , , , , , .

Eric Steckling, Pitney Bowes Business Insight

CompUSA is attempting to neutralize the Internet’s one big advantage: Information. In an effort to improve the retail shopping experience, CompUSA has upgraded 23 of its 32 stores to the “Retail 2.0” version. Chief executive of parent Systemax Technology Products Group Gilbert Fiorentino has designed new product displays that include touch screen computers which provide specifications, pictures, customer reviews, competitor’s prices and other information about the products on display. The idea was to change the passive approach to retail and engage the customer. CompUSA has found that information empowers the customer and allows them to make more informed decisions, which Fiorentio says is translating to loyalty and increased traffic.

So what’s next for “Retail 2.0”? Amazon.com often gets me to buy items by simply suggesting them to me based on items I have in the cart, have already bought or even looked at. These (usually on target) suggestions are generated from a vast database of the browsing and purchasing records of myself and the other 76 million unique visitors last month.   The difference is data. Online retailers have an easier time collecting and storing customer data. Most brick and mortar retailers have been slow to collect or utilize transactional data, which is instrumental in improving stores’ customer experience.

It is evident that technology will play a key roll in helping retailers “engage” their customers. RFID controlled inventory and smart shopping carts could perform the same suggestive functions by identifying items in your cart and making suggestions based on prior customers’ cartloads. To fully leverage transactional information retailers must also know who you are, another task Internet retailers have no trouble with. Once the customer is identified, Retail 2.0 should include social media interaction as well as purchase driven targeted emails. Only time will tell what other innovations brick and mortar retailers will create to slow the market share loss to online vendors.

Real Estate Spotlight on Manhattan: Taking Advantage in a Down Economy

Published on March 18, 2010 in Kyle Bingham. 0 Comments Tags: , , , , , , , , .

Kyle Bingham, Pitney Bowes Business Insight

When describing New York, Frank Sinatra famously said, “If I can make it there, I can make it anywhere.” Simply called “The City” by locals, Manhattan has always been a place that’s been tough to break into for many national retailers, but as rents continue to drop and independent retailers abandon their unprofitable storefronts, now is the time for these national retailers to seize an opportunity. According to various reports, Manhattan’s commercial-lease rates are expected to bottom out in the early part of this year; they are expected to begin rising by late summer.

New Yorkers have unique shopping habits and transportation methods, so a national retailer’s traditional formats may not always work in Manhattan. Success stories are a result of concept flexibility. The drugstore chain Duane Reade famously conquered the landscape with creative store configurations and by giving New Yorkers the products they need, convenient locations, and fast service. Walgreens was so enamored by Duane Reade and their presence in Manhattan that they agreed to buy the chain last month for $1.1 billion. Restaurant chains like Chipotle (19 Manhattan units) have also made a push into Manhattan, with some success. Other major national brands, like The Home Depot and, more recently, Costco, have opened locations in Manhattan to more modest success. Both companies had to drastically change their concept to fit the typical New Yorker: families in SUVs weren’t going to be dropping by to buy a new lawn mower or to fill up their minivans with seven cases of peanut butter; entire departments had to be revamped to add more items that could be carried onto the subway or down the block. Those retailers with smaller footprints, like Starbucks, can be more nimble in the city, filling the spaces that others cannot. Starbucks now has more than 170 units in Manhattan, some famously across the street or around the corner from… another Starbucks. Whether for a public-relations play or for a full-blown strategy, one must enter Manhattan armed with research.

In Manhattan, location is truly king, but simply being in Times Square does not guarantee success. Other factors come into play – factors like street-front access, proximity to a subway access point (stairwell), and corner (as opposed to midblock) location. Even being on an avenue instead of a street can have a huge impact on potential revenues. Daytime population also plays a huge role in a site’s potential; in fact, the highest density of daytime employees in the United States is proximate to the 42nd Street/Madison Avenue intersection, near Grand Central Station. Using our extensive database of employee and daytime population in Manhattan and augmenting it with field research, Pitney Bowes Business Insight is able to effectively serve our New York-bound clients. Techniques used to forecast sales for suburban locations don’t necessarily work in Manhattan: drive-time analysis, for example, gets thrown out the window. When analyzing Manhattan, pedestrian counts and proximity to daytime population become paramount. Operations of the business also can also play more of a role in Manhattan than in other, less dense areas. Specifically, adjusting staffing levels to the time of day and the district is important; after all, the staff necessary for a store in the Financial District may be drastically different from one in the Upper West side.

Over the years, I have learned that successfully analyzing Manhattan requires quality data sources for daytime and employee population, a good understanding of pedestrian patterns, and strong fieldwork – not to mention a little bit of intuition. A good pair of walking shoes helps, too.

Keeping Predictive Models Current: Dealing with Continuous Change…Continuously

Published on March 4, 2010 in Nat Evans. 0 Comments Tags: , , , , , , , .

by Nat Evans, Pitney Bowes Business Insight

Most contemporary predictive models, which forecast performance such as sales, customer visits, membership levels, etc., are based on historical data that create “snapshots in time,” using whatever relevant sources were current at the time of analysis. Examples include POS distributions, store and competitive locations, store sales performance and demographic data. But we know operations and the environment changes as soon as a model is completed and put into use. As a result, model accuracy erodes with each passing day as the data inputs into the model or the benchmarks upon which expected performance are based become stale. To be sure, most site selection professionals and researchers attempt to make sure models are as fresh as possible, updating these data elements on a regular and recurring basis. During recent engagements with several long time clients, we have been asked if there was a way to take into consideration dynamic time series data elements to help with forecasting and minimizing risks.

What do we mean by dynamic data?

Many factors may play pivotal roles in retail forecasting and market prioritization. Depending on the level of aggregation, the obvious thought is that a researcher may be able to affect a change in market conditions or individual sales estimates, depending on the application. Indeed, they can significantly sway analyses enough to change even the simplest of decisions, either minimizing risks (if used appropriately) or increasing a company’s vulnerabilities, especially given the current macro-economic climate.
A couple of sources of dynamic data within the context of a static model may include:

• Macro-economic data such as housing starts, CPI (consumer price indices), funds rates, and unemployment percentages either nationally or at varying levels of macro geography – state, county, or CBSA. Such measures provide a look into the health of consumers’ collective behavior, and depending on how the analysis is structured, whether these factors will be leading or lagging indicators of retail growth and consumer spending (PBBI has created an approach-MarketPulse-that incorporates these factors into predictive models).

• Gas prices. Gas price fluctuations on a regional or even local level can create a similar effect that macro-economic variables may produce in models. Obviously, the higher gas prices rise, the less disposable income consumers will have to purchase goods and services, potentially depressing actual local store performance. Distance may become a stronger deterrent to patronage as a result.

If a retailer’s or restaurant’s sales forecast model was created in better times, it may produce a “false positive,” inappropriately triggering a go/no-go decision and costing company valuable resources and capital from other locations that may be more profitable. Just as importantly, if a company is judging a general or district manager on existing location(s) sales performance based on a projection created earlier in the fiscal year, the company may be unduly influencing that leader’s performance rating on factors outside of his or her control.

How can we create more flexible models using dynamic data?

There exists a myriad of ways we can leverage dynamic data through any forecasting or analytical process, more generally. The important point with any data source is to leverage any and all relationships that may prove fruitful through the forecasting process. But, it must be relevant to your research design, have purpose, and be significant enough to warrant using in modeling and analytical review.

In the future, the ability to collect and cleanse data continuously not only from existing, well-documented sources, but also new sources, such as e-commerce and online social/behavioral data, will become more available and increasingly important across any organization. Additionally, whether on-premise or in the “Cloud”, the technology that facilitates a seamless data flow into predictive applications should enable decision-making with the most up-to-date analysis possible.

Consumer Demographic Profiling: Does Distance-weighting Make a Difference?

Published on November 20, 2009 in Nat Evans. 0 Comments Tags: , , , .

Nat Evans, Pitney Bowes Business Insight

It is a standard market research practice to use psychographic segmentation as a primary tool for discerning a company’s target customer.  This “customer profile” creation is a primary means by which customer behavior is bucketed into distinct groups that reflect differing customer characteristics, shopping behavior and loyalty to a retail, restaurant, or consumer package brand.

Over time, the Strategy & Analytics statistical modeling team at PBBI has given a lot of thought to the idea that customer profiles, and their use in sales forecast models, may be enhanced by weighting the customer source survey data by distance.  It makes sense.  The farther away target (or non-) customers are, the more pronounced the profile scores may be.

For instance, a typical customer profile for a high-end department store, with a specific high income, suburban customer segment or “cluster” (Corporate Clout, say, from Acxiom’s PersonicX lifestage segmentation system) may have a score of 200, meaning that people within the segment spend two times what an average customer spends for the concept.  A low-income segment (Single City Stress, for example) may have an index score of 40, or the segment spends 40 cents for every dollar that an average customer spends. Weighting the profiles by distance, however, may yield a more intensified result.  You may expect the high-income cluster to go from an index score of 200 for customers only within 0 to 3 miles, to 225 for those same customers beyond 6 miles from any given store.  Perhaps the Single City Stress cluster would go from 40 to 25, meaning that the farther away the cluster is from the store, the less they are willing to patronize and spend at the department store relative to other customer segments at the same distance.

In theory, it seems to be a reasonably insightful approach.  In practice, the S&A modeling team created just such an analysis, and found that among several clients’ customer databases, distance has no significant bearing on the relative spend of psychographic segments at the same distance.  The following box plot will give a sense for one sample profile’s distribution:

Distance Weighted
As shown, 50% of all scores’ distributions fall between approximately 50 and 110.  A couple of outlying clusters find themselves floating outside the distributions (the “1”, “2”, or “3” above the whisker for each plot), but statistically, no significant difference was found between scores at different distance increments.  The distributions’ medians were roughly the same; variance was the same.  This pattern was consistent among several customer files we tested, and the application of several distance weighting methods yielded no statistically significant enhancement whatsoever.  Goes against the hypothesis.  To be sure, there exists a multitude of ways to carve up customer data, and this analysis is by no means definitive, but from a macro level, it seems the proof is in the data. This analysis also does not mean that distance in its myriad forms (straight-line, drive time, drive distance) has no influence.  Obviously, it does.  Distance decay portrayed on a sales per capita, or other relevant, basis is very important indeed, and is an extremely well documented predictor of consumer behavior.  It’s just a matter of proper application, and what any one retailer’s customer data is truly telling an analytics researcher.

PBBI Retail Practice Leader Appears in Retail Traffic Magazine

Published on November 16, 2009 in Leslie Nogue. 0 Comments Tags: , , , , .

In the October issue of Retail Traffic, Associate Editor Elaine Misonzhnik interviewed Devon Wolfe, Managing Director of Americas Strategy and Analytics Services with Pitney Bowes Business Insight, for her story on current site selection trends.

In the article Forced to Count Every Dollar, Retailers Re-evaluate Site Selection Practices, Devon assesses the current state of retail site selection, which is showing signs of growth, despite the economic downturn. In today’s economy, retailers are holding themselves to much more stringent criteria when assessing the viability of a new location. The industry push for accurate, up-to-the-minute information on a market by market level highlights the importance of macroeconomic data when retailers are evaluating market potential for new stores. Today, retailers need visibility into “statistics on employment figures, GDP growth, retail sales and the number of bankruptcy filings”. It is for this reason that Pitney Bowes Business Insight introduced MarketPulse, a quarterly subscription to a detailed macroeconomic report that provides insight into market level trends. [Read entire article...]

Retail Traffic is a monthly magazine written for senior level retail executives.

Attack Back With Financial Literacy

Published on November 11, 2009 in Brian Diepold. 0 Comments Tags: , , , , , , .

Brian Diepold, Pitney Bowes Business Insight

You couldn’t go ten minutes at BAI Retail Delivery without hearing about – or talking about – NSF fees. It’s natural that it would be a hot topic as it is certainly getting its share of media and congressional attention these days. Richard Davis made a great point that the industry needs to educate Congress and the public that these fees are not necessarily immoral – after all, as he so nicely pointed out, we are providing a service for the consumer and we are charging for that service.  I agree, and we need to take Mr. Davis’ advice that we need to tell the story in a more positive light.

I also think it’s important that we do more to educate our consumers. This economic crisis is very tightly linked to the lack of economic education and financial literacy in our country. We don’t do enough as a society to arm our population with the necessary tools to think about the world the same way we do as bankers, financial advisers, and economists. Not everyone needs to have a passion for these topics, but they certainly need to have a basic understanding in order to manage their personal finances. The national and state councils on economic education do everything they can to support these initiatives for our youth, but we also have an adult population that lacks this knowledge.

Let’s take it upon ourselves to help solve that problem. Banks could generate goodwill by offering simple educational programs at the point of sale. Let’s take 15 minutes to teach a new customer how to use their checking account. This may just allow them to avoid the extra fees down the road, while at the same time allowing you to guide them to being a profitable customer in other ways.

Not only is it good for the customer, but it would have to go a long way to convincing Washington that we are serious about addressing the issue ourselves – without Congress imposing their own solution.

Worst case – you are the only bank in your market that makes this effort. In that case, it should allow you to differentiate your offering and build that goodwill or brand value with the market. It’s a win-win.

Are American Retailers Ready for a Universal Reward Program?

Published on November 9, 2009 in Eric Steckling. 0 Comments Tags: , , , , .

Eric J. Steckling, Pitney Bowes Business Insight

As Democrats work toward a universal healthcare system for America, should American retailers take a cue from Canada and support a universal rewards program?

The Air Miles reward program in Canada has been in business for about 17 years and is supported by over 100 retailers (including retailers in the U.K., Spain, the Netherlands and several Middle Eastern countries). The Air Miles program has a fanatical following among its 9.5 million collectors. Parent company LoyaltyOne touts that 97% of Canadians know about the Air Miles program. So if the program is so successful in Canada why hasn’t a similar program been deployed state side? Well, they tried. The Air Miles program was introduced in the U.S. at the same time as the Canadian version in 1992, and was picked up by several national retailers. The U.S. program was shortly there after deemed unprofitable and discontinued in May 1993.

American retailers understand the value of customer loyalty programs, and many companies have developed their own programs. We are all familiar with Delta Skymiles, the Kroger card, CVS ExtraCare and our credit card’s Reward Points systems. Just take a look on your key chain or in your wallet. How many loyalty cards do you carry around every day? Retailers and consumers could benefit from a more universal system. The idea is simple: customers sign up for one program and are able to trash their wallet full of cards. Retailers join on the program and dole out the “points” at their discretion, and then benefit from a larger base of customers carrying a universal card. This will allow participating retailers collect more data about their customer’s shopping patterns than with a proprietary system. It will also allow smaller regional retailers to join into a loyalty program rather than create their own from scratch. As simple as the idea sounds, implementation of such a system would face many challenges and push back from multiple constituents, including retailers worried about margins or derailing their existing reward program and consumers wary of giving out personal information or losing benefits they have already earned.

The whole truth is that for retailers, the customer data that is collected from a reward program may be more valuable than the loyalty they generate. Participation in a universal program would mean more data for all. Those of us in the predictive analytics field are well aware of the value and usefulness of recording point-of-sale data and being able to link it with a specific customer. The retailers who collect and use this data gain efficiency in efforts including marketing, store planning, and product promotion to name a few. The barriers for a universal system are high, and pose a chicken and the egg dilemma between consumers and retailers: Without the critical mass of supporting retailers, consumers have no need to participate in the program. If the consumers are not signed up and participating, then where is the benefit for the retailers? And would Americans willingly supply one “big brother” company with all their spending data?

This initial failure of the Air Miles program in the U.S. may have been in part due to a translation issue. What do airline miles have to do with gas or groceries? Or an American need for instant gratification, why collect points when I could save money NOW?! One would think that if the program is so popular north of the border with our metric neighbors, shouldn’t it be called Air Kilometers?

The Value of Fielded Evaluations in the Site Selection Process

Published on October 27, 2009 in Ed Borden. 0 Comments Tags: , , , , , .

Ed Borden, Pitney Bowes Business Insight

Do you ever miss a football game, but read the stats after the game and say “wow, that was a pretty close game – final score 23 -21”. However, if you had actually seen the game in person you would have realized that one team dominated the game for three quarters, but only by a series of miss steps, did the second team have the ability to win the game at the last minute. We see this happen every weekend in the fall – the stats and numbers alone do not provide you with the full flavor and scope of the game… who was better or was the victory deserved. This is similar to the site selection process.

Far too often, businesses are so focus on the numbers, demographics/psychographics characteristics, traffic counts, distance to the nearest competitor, etc. that they do not value the intangible, qualitative aspects of a potential site that can only be garnered from an impartial fielded site evaluation. Even if you are visiting a proposed deployment site for a day, you can gain true insight for answering the questions:

  • How good is the ease of access and traffic patterns around the proposed site?
  • Do the surrounding neighborhoods appear to be trending up or trending down (are the homes well maintained or are there foreclosures)?
  • Are there demographic barriers to the site? – “don’t be caught on the wrong side of the tracks”
  • Do the surrounding shopping centers appear to be stable or are they losing retailers (especially national nameplates)?

Because of this intangible, difficult to generate in-house data, we believe that an impartial fielded evaluation of the site should always be conducted. This fielded evaluation can be done by either an outside organization or by an in-house research team. Too often field evaluations are left strictly to the real estate teams, who may not be completely impartial, as they typically have a vested (and compensated) interest in the new deployment (whether successful or not). Our organization has done fielded evaluations for many, many clients and has effectively seen most of the US and Canada, consequentially we have market knowledge that others do not and we can better judge one site versus another more objectively.

Whether you are opening a retail outlet, restaurant, bank or health center, in these challenging economic times, when it is so crucial that new units open to plan, there is real value in paying the relatively low cost of airfare, lodging and time for an impartial professional, either internal or external, to see the site and provide the “flavor” of that site to the forecast, and not to just rely on the in-office generated numbers.