By David Kelly, President/CEO, AnalyticsIQ, Inc.

AIQ’s joint product with Experian (“DSE”) has gotten some
interesting attention lately:

http://adage.com/article/adagestat/u-s-households-lack-discretionary-spending-power/227810/

http://www.experian.com/blogs/marketing-forward/2011/05/31/understanding-consumers-by-discretionary-spend/

This product leverages AIQ’s analytics and Experian/AIQ data to produce a score that predicts annualized household spending on non-vital items.  These items include things like dining out, alcohol, books, entertainment, etc.

At a macro level, AIQ has found that discretionary spending has stabilized after a precipitous drop last year:

DSE incorporates demographic, financial, economic and survey data to produce the most accurate household-level prediction of discretionary spending.

By Gregg Weldon, Chief Analytical Officer, AnalyticsIQ, Inc.

With housing prices across the country in what seems like a free-fall, it’s interesting to note which areas have seen the biggest drops since 2000.  Michigan has been hit the hardest by the price depreciation, thanks to job losses, manufacturing contraction, and the continual migration by the US population to the Sunbelt.

The Freddie Mac Index shows that the CBSAs (Core Based Statistical Areas) with the biggest decreases in home prices since 2000 are:

1. Detroit-Warren-Livonia MI 65.51
2. Flint MI 65.95
3. Monroe MI 70.20
4. Jackson MI 74.13
5. Muskegon-Norton Shores MI 77.19

This means that a typical house in Detroit is now worth 65.51% of what it was worth in 2000.  Shockingly, the bottom 5 are all in the state of Michigan!

At the other end of the scale, some areas of the country, while adversely affected by the economy, still have housing prices much higher than they were ten years ago.

1. District of Columbia 229.07
2. Ocean City NJ 201.00
3. Honolulu HI 200.67
4. Midland TX 184.11
5. Casper WY 177.28

The median value for the Home Price Index since 2000 is 123, meaning that, in most areas, homeowners are still slightly better off with their homes than they were 10 years ago.  However, just a few years ago, homeowners were seeing their homes double in value every 7-10 years.  We’re obviously living in a different world today.

By Mike Hattub, Chief Operating Officer, AnalyticsIQ, Inc.

The online marketplace is a vast and continuous marketing arena.  There are always consumers online for various reasons, whether simply scanning the web or specifically looking for information, products, or services.  However, no matter the reason, there is always a need to use data to learn more about these consumers.  This allows marketers a better chance of connecting with a valuable audience at a time when they are a few clicks away from buying.

External enhancement data (i.e. Wealth, Spending, Estimated Credit Risk, Income) and models can be married to online consumers in a variety of ways once they have registered online either now or at some point in the past via online various online forms or ad network registration.  This creates the ability for consumer address/phone/email to be linked to their name.  Then, external data and modeling can be used to enhance consumers by matching on some or all of these pieces of information. 

If a consumer is filling out a web form to apply/inquire about a specific product or service, then external data can drive what level of offer to propose and modeling can determine how to prioritize each given lead that is generated.  If a consumer is simply in an ad network that knows who they are, then external enhancement data can be used to customize which ads are served to the web pages that they are visiting.

These are a few examples of how enhancement data can improve online marketing strategies.

Dave Kelly, President, AnalyticsIQ, Inc.

The Harvard Business Review published an interesting survey of 2,241 US companies representing 1.25MM sales leads.  Given the ‘real time’ emphasis of today’s business environment, the results were shocking:

• -The average response time for an online lead was 42 hours
• -23% of online leads never receive a response

 Also interesting was the value of immediate response:

• -Leads contacted within an hour were seven times more likely to qualify  as leads contacted after an hour
• -Leads contacted within an hour were sixty times more likely to qualify  as leads contact after 24 hours

 Clearly, online leads require a commitment to immediate response.  How?  Leverage technology to provide ‘triage’ on the lead stream.  Leads that closely fit the company’s unique offering should be placed at the top of the queue, whereas leads that look less promising can be given a lower priority.

By Mike Hattub, Chief Operating Officer, AnalyticsIQ, Inc.

Having begun a career in modeling and analytics in the United States back in 1994 working with a U.S. consumer credit bureau, 100% of the work completed was based on U.S. data to solve U.S. business problems.  This was a great way to start a career since a consumer credit bureau has tons of data to analyze.  Additionally, the U.S. was far along on using data in complex modeling solutions for both risk and marketing applications.

Over the last several years, our modeling and analytics capabilities have expanded into many other countries across the globe.  Specifically, projects have been completed in 5 continents for banks, insurance companies, and retail organizations.  While languages and cultures vary greatly from country to country, the business problems being solved across the globe with modeling and analytics are very similar.  To further explain, some countries have much more data than others whether this refers to external (public) data or internal (client) data.  However, at the end of the day, once a modeling dataset is created, the problems being tackled are very similar.

So, having experience across the globe will create even more exciting opportunities to expand business and partnerships in the years ahead.

By Gregg Weldon, Chief Analytical Officer, AnalyticsIQ, Inc.

The latest economic numbers are in for the third quarter of 2010 (ending September 30) and some interesting figures have presented themselves.  In most CBSAs (“Core Based Statistical Areas”), the savings rate among individuals has decreased, reversing a trend of increasing savings that we’ve seen for the past several years.  It also appears that retail sales has continued to grow (at a tepid rate), meaning that, for many people, new spending is being financed directly by their savings accounts/retirement funds.

On the surface, this bodes ill for the economic health of the country.  However, the latest numbers also show some encouraging signs relating to home prices and unemployment rates.  This leads us to two distinct possibilities; one: that people are in such dire straits that they’re now spending what little savings they have left in order to maintain their lifestyles; two: that people see a light at the end of the tunnel for their personal financial situations and they’re now comfortable enough to begin spending again.  Obviously, there are people in the country that fall into both of these extremes.  It will be interesting to see, over the next few months, which way the overall economy is tilting.

By Dave Kelly, President, AnalyticsIQ, Inc.

We at AIQ have generally seen a drop in response rates for our clients using email.  The obvious challenge is ‘over fishing’ in the pond of online consumers by many entities sending numerous emails to consumers.  There is no doubt that sending multiple emails to a consumer over a short period of time does more harm than good (for a reputable marketer) – a very small percentage buy anything and an increasing portion ‘opt out’ or report the company as a ‘spammer’.  Certainly, this does not do wonders for a consumer brand…..

One answer is to use a segmentation tool to match an applicable message, offer, price, and/or product to an individual consumer.  How does this work?  A good segmentation tool (such as AIQ’s Delineate™) will class consumers into homogeneous groups, with similar wants, needs and desires.  And while there are still some major differences between people within these groups, they are a lot closer together than would otherwise be found.

A simple historical analysis can match response history for different messages, products, etc. to the most applicable cluster (see chart below).

While greatly simplified, the above chart conveys the basic idea – you determine which message, price, etc. you match to each cluster based on historical analysis and/or ongoing testing.

What can this approach net?  We have seen increases of 20 to 30% in response, along with even great decreases in opt-outs.

By Gregg Weldon, Chief Analytical Officer, AnalyticsIQ, Inc.

 One measure of the relative strength of the U.S. economy is the growth in retail sales from quarter to quarter.  These 3 month changes serve as a leading indicator for where the national economy is headed in the near-term.  Although the U.S. economy changes over time, it’s also revealing to look at changes in CBSAs around the country.  These CBSAs (“Core Based Statistical Areas”) are made up of metropolitan areas (cities, towns, unincorporated areas) that serve as indicators for how well individual portions of the country are coping with stress and/or succeeding in growing the economy.

The entire country experienced a huge drop in retail sales in 4Q08, when the extent of the housing crisis and accompanying Wall Street meltdown first became apparent.  It’s interesting to note, however, how portions of the country arrived at that point, as well as how they’ve recovered since then.

Each quarter, all CBSAs are divided into performance deciles, in which they’re graded based on such economic measures as housing starts, unemployment, savings rates, home sales, bankruptcy filings, and net migration, among others.  Group A represents the 10% of the CBSAs that are the strongest in the country, while Group J is made up of the economically weakest.  These groupings change each quarter, so that Group A is always the “best” the U.S. has to offer at that point in time, while Group J is always made up of the stragglers.

The chart below shows that, prior to 4Q08, retail sales growth was dropping/stagnant for several periods across the board.  Sales were increasing, but at a decreasing rate.  The gap between Group A and Group J was relatively wide.  Since 4Q08, retail sales have returned to a positive value, although that gap remains.  Also note that, following an initial burst in sales through 3Q09/4Q09, sales growth has once again stagnated/fallen.

Retail Sales Growth

By Dave Kelly, President, AnalyticsIQ, Inc.

 As we continue to position ourselves in the ‘online lead scoring’ space, I have come to the conclusion that there are three key areas of importance in terms of delivering a great product:

1. Technology:  To me, this consists of a firm’s ability to consistently deliver a result in a sub-second and to accurately match the input data (i.e. address) to a marketing database.
2. Analytics:  This refers to the customization of ‘generic’ data to the end user.  Usually, this is in the form of a statistical model.
3. Data:  The marketing database that you are accessing in real-time.

 Fundamentally, the end-user wants to access data that helps them make better business decisions.  Analytics is a way of translating the data to better fit the end-user’s needs.  Technology is the means of facilitating the delivery of applicable data to the end-user.

 While I could be accused of having a bias, I believe that the technology and data elements are virtual commodities – plenty of chances to mess up, but not a lot of upside.  Of the three factors, analytics is the single area where a competitive advantage can be built.

By Mike Hattub, Chief Operating Officer, AnalyticsIQ, Inc.

 Well, 2010 is coming to a close and it is time to see what lays ahead in 2011.  Hopefully, the economy and the country as a whole will continue to recover over the course of 2011.

One very clear direction that is being observed is the ever-growing importance of data and analytics in every facet of the business world. 

From direct mail to telemarketing to email, from ad-serving to lead scoring, from social networking to addressable ads, from risk management to loss mitigation, data and analytics are being used without exception.  Data is of the utmost importance in optimizing any of these aforementioned applications and modeling & analytics is the key to making the data work wonders.

As the market continues to recover, the need for data will continue to expand, and the mining of data will become more and more exciting in the year ahead.