No industry player, including the demographic data companies, seem to have gotten a handle on the place of geographic level data in this new world order.However, let's not feel bad, conversely no CRM company has really grasped the opportunities either.This still leaves the data companies in GIS staring across the table at the CRM players, with the GIS software providers sitting in the middle wondering who is going to make the next move.>
While I do not pretend to be presenting you the panacea to solve this quirk in the industry we are facing, I do want to argue that I believe there is significant relevance of geographic data in the CRM world>
So why do I believe geographic data is relevant in the CRM age?
Privacy please...
In-depth discussions on consumer privacy are not commonplace in the
GIS world; the prevailing feeling is that the industry is immunized from
legislation and curbs on privacy.Well that opinion certainly does have
some merits, but the other side of that is that geographic data stands
to be a beneficiary of the prevailing mood on consumer privacy.All signs
point to consumer privacy being an issue of some significance in Congress
in the coming session or two.It is possible that further Congressional
oversight in the usage of data, particularly credit derived data, for consumer
marketing purposes could see an increased restriction in the ability of
companies to use this data to find new customers and secure their business.
While I do not pretend to be a government affairs executive or a Washington DC 'K Street' Lobbyist, there are three key reasons why I believe greater privacy restrictions are inevitable:
- Consumer privacy is a win/win issue for politicians.Recent elections have shown how a politician can utilize consumer privacy to build profile and bring voters to their cause.Bottom line - no politician is going to lose an election because they are for more consumer privacy.
- Corporate reputations have been damaged and faith in corporate responsibility is low.Recent accounting scandals and shaky profit performances have made corporations big targets for regulation and restriction.
- Self-regulation of the industry is not something that reassures people sufficiently.More regulation is almost inevitable; time after time we see that self-regulated industries are targets for Congressional or Federal over-sight because they have failed to truly regulate themselves.
Its all about the coverage - Household data
Household databases are renowned for the somewhat patchy coverage of
variables.For example, while many consider the big consumer marketing
databases to have actual household information, it would surprise many
to learn that many of the variables associated with a household are actually
statistical models or projections - often based on geographic data!
For example, a demographic variable such as income is often based on less than 20% actual information on a household income.This "actual" information is usually self-reported by the consumer, which we know to be a less than 100% accurate means of gathering data on income.Finally, the key point is that this self-reported data is then joined with Census-derived income variables to create a statistical model, not actual information.If this is the case, why should geo-level data be discounted in favor of this kind of data?
Customer data is as customer data does
Just as compiled marketing databases have their coverage issues, so
does customer data and customer transactional data.If the company is new
to a market, region, product line or area there are going to be challenges
creating a 1 to 1 transference of the existing customer knowledge to this
new area.Secondly, we know coverage is an issue for compiled marketing
databases at the household level, well coverage is certainly an issue for
customer data also.
Customer data, however, is an incredibly valuable tool in a number of
business planning activities, but it should be viewed as a source that
will often times need supplementing.Geo-level data offers an excellent
source of contributory information at a reasonable cost-point.
Cost-effectiveness
This leads me to a key business point: geographic level data, be it
demographic or consumer behavior or even business related, offers excellent
value for the money in these cost-conscious times in which we work.The
cost effectiveness is further enhanced when the prices of geographic data
is compared to household data or custom market research data.
The data quality discussion
Over the last couple of years we have seen increased traffic in the
long-standing debate over what data is the best quality or how accurate
the respective data sources are.While I do not intend to respond to many
of the points that have been raised about geo-level data quality, I want
to point out some key points on data quality and how they relate to this
discussion.
Perhaps the single most important fact that so many forget is that data quality is not a simple question that has a yes or no answer.It is a complex, multi-faceted problem with multiple answers.This means quite simply that there is currently no definitive answer to data quality and thereby no means for us to feel that geo-level data is inferior quality to other sources of information.
Secondly, other sources of data suffer from exactly the same challenges that geo-level data does.There are situations in the collection of data, be it Census or compiled elsewhere, that need to be overcome.There are situations coming from the measurement of growth and change that all data compliers and users must navigate.There are many things that can affect data quality, in fact, some household or person level data sources suffer from more problems than geo-level data.Leading to the thought that perhaps there is a reverse argument about geo-level data being better quality.
In addition, the majority of geo-level data, particularly Census-derived demographics, have a firm basis in widespread actual information (not modeled) and are regularly updated through highly developed modeling processes that have been established over the last 30 years.
The bottom line is that the discussion on data quality and accuracy will continue, but there is no reason why the geo-level data should be inferior from a quality perspective.All data must be judged along the following dimensions: price paid, end use objective, sources and methodology, and application.It is my feeling that at the appropriate time for the appropriate reason, geo-level data offers excellent quality and value for money even today in this increasingly CRM-centric world.
Inter-related data and some final thoughts
I have touched on a broad range of disparate ideas, but the overall
theme I am trying to stress is that as the market changes geo-level data
has an important role to play.Now more than ever, value and cost-effectiveness
are crucial watchwords for successful business.Now more than ever it is
important to challenge the assumptions under which business operates; just
because geo-level data has been around for a while does not mean that it
cannot play a valued role in today's market.
Let me conclude with a final disclaimer and call-to-arms: I encourage all my colleagues to contribute to this debate with their thoughts and ideas.For continued growth and success, the GIS and Micromarketing arenas must confront the challenges out there; our businesses and markets need to be constantly evolving to ensure that we stay relevant; relevant to technological advances and relevant to the needs of the end-user.