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Chapter 4.3 : Managing and using the B2B database (ensuring data quality and cost)
Chapter 4.3
Managing and using the B2B
database (ensuring data quality
and cost)
This chapter includes:
J
Why database management is important
J
How to acquire data for your marketing database
J
How to keep that data accurate and useful
J
How to segment and profile your data
J
What is data protection legislation and how to comply with it
About this chapter
C
hapter 4.1 has already provided an overview of database technology for the
direct marketer; while the principles it contains are entirely general, it has
been written mostly from the point of view of a B2C marketer, with just a
short reference to the particular issues of B2B. This chapter builds upon the
general concepts outlined in 4.1 to provide a similar picture seen through the eyes
of a B2B marketer.
Author/Consultant: Simon Lawrence
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Chapter 4.3 : Managing and using the B2B database (ensuring data quality and cost)
Simon Lawrence, MD, Information Arts
Simon Lawrence is the
Founder and Joint
Managing Director of
Information Arts, the UK’s
leading business-tobusiness database
marketing solutions company.
was, and this vision has been realised in the six
years since. Information Arts has been very active
in raising the profile of business-to-business
database marketing through launching a range
of innovative products and services and by
defining a new standard of best practice.
Over 17 years of working in business-to-business
marketing, Simon held senior business
development, general management and
commercial roles at TDS Group and Emap
Business Communications, before founding
Information Arts in 1999.
Simon’s initiatives at Information Arts include two
innovative profiling products: DNA and GIC. He
has also led the way with the annual
Business2Business Conference, which is now in its
third year, the B2B Awards, and a quarterly small
business best-practice forum for non-competing
companies.
He set up the company because he passionately
believed that business-to-business database
marketing could be done more effectively than it
Simon is active within the IDM. He is a member of
the B2B Council and he delivers business-tobusiness content for several training modules.
Chapter 4.3
Managing and using the B2B
database (ensuring data quality
and cost)
Why database management is important
T
oo much of the money that is spent on database software is wasted. It
happens in both small and large companies, and with both consumer and
business-to-business campaigns.
The marketing department invests significant sums of money in new software,
expecting that it will help them target their direct marketing more effectively; then
they fail to manage the database properly, they don’t see the expected
improvement in results, and before long they are blaming the software and
looking around for an even more expensive solution.
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Don’t spend any more money on database software until you have improved
the management of your existing database
In some cases this happens because of the economic cycle. Companies invest in
software in the good times and then lack the resources to manage it through the
bad times.
In other cases it is because too many marketers see data as less important than
creative. They forget that the best creative in the world is useless if sent to the
wrong person.
Very often though, this waste of time, money and potential occurs because the
marketer simply does not know how to manage a database.
This chapter will show you how to avoid this trap, covering the four essential
areas:
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Acquiring data
G
Maintaining data
G
Using data
G
Staying on the right side of data protection laws
How to acquire data for your marketing database
What data to collect
Companies want data on their customers in order to keep them and to sell them
more. They also want data on prospects, those people who are not their
customers, in order to turn them into customers.
Broadly speaking, you want to get as much information as possible about both
customers and prospects. However, it is possible to have too much data, if that
data is not organised into a useable format. For example, it is generally better to
have 100 names with addresses than 1000 names without addresses.
The first step in managing a database, therefore, is to ascertain who you want on
your database and what you need to know about them. Most marketers begin with
existing customers and build up the following basic facts:
G
Company name
G
Address
G
Telephone number
G
Website
G
Industry sector
The most commonly used breakdown of industry sectors is the Standard
Industrial Classification (SIC) codes.
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Once that basic level has been established, then you can begin to gather more
detailed information such as:
G
Transaction history (what they bought from you and when)
G
Relationship history (what has been discussed and with whom)
G
Account history (what they have paid, when, and by what means)
G
Marketing history (response to previous marketing campaigns)
G
Company turnover
G
Number of employees
G
Head office or branch
G
Contact names
G
Email addresses
Where to get it from
For your existing customers you will probably already have most of this
information in other systems such as accounts and sales databases. However,
when it comes to building a prospect database you will almost certainly need to
acquire the data from a third party.
While there are around 2,000 lists of businesses in the UK, the business-tobusiness marketer faces particular problems in building his or her own prospect
marketing database. The greatest is that while consumer marketers can use
census data, there is nothing comparable for the business-to-business marketer.
In the absence of a central register of all businesses in the UK, you will have to
rely primarily on the following three types of marketing data:
1)
Compiled data
Most commonly this comes from BT’s OSIS file. OSIS stands for Operator Service
Information System, and it is a database of every telephone connection in the UK,
both business and consumer. BT licenses the data to the big directory publishers,
who are Yellow Pages/Yell, Scoot and Thomson Directories.
These organisations then telephone each of the business entries on OSIS to find
out the appropriate SIC code and the number of employees and to gain
permission for the data to be used for marketing. They then sublicense the data to
a large number of marketing services companies, from whom you can buy it.
There are two major problems with this type of data; one is that OSIS misses the
1.5 million or so home-based businesses that do not register for a business
service from BT and the other is that OSIS provides only very basic data. In most
cases you will need to combine it with one of the other two types of business data.
2)
Companies House
Legally every publicly and privately limited company must register their business
and directors’ information at Companies House. They must also file their financial
information there once a year. This is a rich source of information, particularly on
large corporates. However, there is very little information on the self-employed, on
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sole traders, or on partnerships, and there is nothing at all on public sector
bodies.
3)
Lists of subscribers to magazines and exhibitions
These do not provide large volumes or comprehensive coverage but can be a good
source of more detailed information such as contact details for middle
management decision makers. A major problem is that contacts on them have
often exaggerated their job responsibilities in order to receive a free magazine.
The ideal is a combination of all three data types, but in most cases this is
difficult to achieve. The main obstacle is that very few lists contain answers to
exactly the same questions, and even fewer do so in the same formats. On a
simple level, while one magazine publisher might gather the surnames and initials
of its subscribers, another will gather their surnames and full first names.
Aggregating the two lists together without creating duplicates is challenging.
Replicating this across many lists becomes extremely difficult.
Yet, this is just what you as a business-to-business marketer must do if you are to
build a prospect database. You may be able to gather some data on prospective
customers through your own sweepstakes, contests, online registrations and
other lead generation activities but it will be limited, and so you will need to buy
in data for any large-scale marketing campaigns.
Don’t make the mistake of thinking that the cheapest list will be the best
value list. Ask yourself why it is so cheap, and always think in terms of
return on investment
Very often you will find that you need to supplement your existing data and the
data you buy with a bespoke telemarketing campaign. A particular problem for
business-to-business data that often requires a telemarketing solution is gaining
contact level data. Mail that is addressed to an anonymous job title tends to end
up in the bin, while mail sent to a named person will often be opened, even if
there are other minor mistakes on the address.
However, there is little in the way of reliable contact level data on most businessto-business lists, so you may find that telemarketing is the only way to acquire it.
Telemarketing is expensive and so you need to consider carefully whether the
likely return from your campaign will justify the expenditure.
Renting data is less expensive than buying it
With most lists you can either rent or buy them. Renting them allows you to
use the names once, and you cannot add them to your own database, unless
you receive a response to your approach. Buying them gives you unlimited
usage.
If you want to build a long-term relationship with your prospects you may
need to buy the data so you can generate several points of contact each year.
However, if you are aiming for a simple one-hit campaign then renting lists is
often sufficient and tends to cost much less.
Even if you do plan to recontact the companies on your list you might still
consider renting it and making such a generous offer to them on first contact
that a very high proportion of them respond.
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Who to buy it from
There are many people who will offer you advice and assistance on buying data.
You can buy your data from an original source, such as a publisher. By doing this
you will avoid paying a middle man, you know exactly where it’s come from, and,
by discussing your needs, you may even be able to influence the data that that
source collects in the future.
While there are many reputable providers selling excellent, high-quality lists,
there are just as many less reputable providers looking to make quick profits
on poorly-researched, inaccurate lists. The Direct Marketing Association
(DMA) has two kitemarks that can help reassure you in this area.
The DMA List Warranty Register provides evidence that the information has
been collected legally. While widely used, it offers no assurance on the
quality of the data.
The DMA Business List Audit (BLA) was set up towards the end of 2004 to
address concerns over the accuracy of data in business-to-business lists. The
BLA audits the transparency of the processes used by list owners to compile
their lists.
Applicants complete an online accreditation questionnaire, covering issues
such as how often their marketing data is verified and to what extent,
whether they use hygiene systems and screen against the relevant Preference
Service files, and their systems for managing deletions and gone aways. All
this information is backed up with a site visit by the DMA Compliance and
Best Practice units.
After a year, only around ten list owner companies, representing around five
per cent of the market, had gained this accreditation. While the DMA expects
this to grow substantially in 2006, it looks likely to remain a small
proportion of the market, and so it looks as though, in the short term at
least, the best way for a marketer to be confident of data quality is to buy
through a reputable data expert.
Alternatively, you can go to a broker or a consultancy. They tend to have a good
overview of the market, so can advise you on what is available and what is most
appropriate for your needs. They do, of course, charge a fee for their services and
this will be reflected in the cost of the list you buy.
A value reseller will help you tailor a list from a variety of sources and will add
another layer of information. For instance, Information Arts offers its own
Geodemographic Industrial Classification (GIC), which reflects the impact location
can have on a business, and so helps inform your marketing campaigns.
A final option is a co-operative database such as the B2B Alliance. Members join
the Alliance for free, and then regularly refresh their own data within the
collective pot. They can then pay to take out parts of this up-to-date information
and use it in their own campaigns. Launched in November 2004, following a
similar successful model in the US, within a year the B2B Alliance had 40
members.
A similar system has operated in the charity sector for several years. Called
Reciprocate, it has provided many charities with inexpensive and relevant data,
but has led some recipients of charity mailings to complain that donating to one
charity leads to a deluge of mail from other charities.
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Consider buying online
If you know exactly what data you want, you might be able to buy it most
cheaply online. Companies such as Marketingfile, D&B and Experian now
have online purchasing facilities for business-to-business data. Generally,
they contain basic information but are very competitive on price.
Before jumping into this, however, consider that you will not receive the
advice of a list expert, and that you might not be buying the perfect list for
you. Bear in mind also that there is normally a delay of a few months
between the list owners gathering the data and them uploading it to their
websites.
Key points on acquiring data
Data on existing customers is usually the best starting point
Begin by collating and standardising core data on your customers
You can buy compiled data, Companies House data and lists of subscribers
Aggregating all three is ideal but can be difficult
Supplementing it with telemarketing is expensive, but often necessary,
particularly for contact level data
You can buy from the source, brokers, value-added resellers, or cooperatives
Quality marks can give you confidence in the data you are buying
Buying online and renting data can be good ways to save money
How to keep that data accurate and useful
Once you have built your high quality database you need to establish procedures
to maintain the accuracy of the data. Mail that is wrongly addressed will never
reach its target. Mail that contains basic errors, such as name spelling, will never
impress a potential customer. Sending the same mailer more than once to the
same prospect will probably damage rather than enhance your chances of winning
business from that prospect.
As well as preventing your colleagues from inputting errors or duplicates to your
database, you also need to keep track of changes to your prospects. On average,
business-to-business data is subject to an annual 22 per cent decay rate purely
due to staff turnover.
On top of those contacts who leave their jobs, you also need to consider the
people who take maternity leave, as well as those who move to new jobs within
companies, relocate overseas, and so on. In any given year your data can decay by
up to 40 per cent simply because you have failed to keep up with these changes.
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Chapter 4.3 : Managing and using the B2B database (ensuring data quality and cost)
Failure to maintain a database leads to wasted mail packs, wasted postage, wasted
time and wasted opportunities. It can also destroy your reputation among your
prospects. Basically, you can never afford to relax with business data.
Always check the quality of data you import
Just recently I witnessed a highly successful blue-chip company sending out
over twenty mailings to the same customer. Database procedures meant that
every time the customer ordered a new piece of work the company created a
new account. This data was then transferred through to marketing, and that
department failed to check the quality of this data and so missed all the
duplicates.
The basics
Tackling data quality piecemeal is not enough. You need a data strategy. You need
to begin by imposing standard formats for all of the data that comes in and goes
out of your database. Define the essential fields such as first name, last name,
company, town, telephone number and SIC code. Then impose one standard data
inputting process.
You need to ensure that there is one way in for data and one way out. Too many
companies have hundreds of people adding information to their database, and
inevitably everyone does it differently, with varying levels of care and attention,
and so the quality varies. By installing an ‘airlock’ between your colleagues and
your data you will be able to maintain the quality.
Suppression files
You should also clean all of your data against at least two of the industry’s
suppression files. The first is the Corporate Telephone Preference Service (CTPS)
and you must suppress against this file. It is a national register of companies that
have declared that they do not wish to receive unsolicited sales and marketing
telephone calls. It is in fact illegal to make such calls to numbers registered on the
CTPS. (This file is held and maintained by the DMA.)
The second is the Business Suppression File and is simply best practice. This
product comes from the REaD Group and is derived from data and gone away
information sourced from Companies House as well as other business database
owners and mailers. Its six million records include details of dormant companies
and those who have gone out of business, as well as relocations and details of
directors who have resigned.
Software
There are several address management systems that can help with basic address
integrity. However, these systems all use a compressed version of PAF, which is
the Royal Mail’s database of delivery points, and so do not recognise most
business names, particularly those of smaller businesses.
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To tackle this problem, Information Arts has developed an address management
tool called Streetwise, which is designed only for business data. Basically this
doubles the number of companies that PAF recognises and so produces twice as
many business addresses.
Chapter 4.3 : Managing and using the B2B database (ensuring data quality and cost)
There are just as many software packages which can help with deduplication. To
give just one example, helpIT uses ‘fuzzy matching’ technology. It tracks records
based on spelling and phonetics so would realise that Bill Shore at the BBC is a
duplicate of William Shaw at the British Broadcasting Corporation. This sort of
software can only go so far though, and in many cases you will need to pay for a
manual deduplication.
There is such a thing as too much data
Contrary to the views of too many direct marketers, you can have too much
data. We have seen how time consuming and costly it is to keep data
accurate and up to date. It pays therefore to keep only the data which is
actually useful. Companies that refuse to discard their hard-earned data tend
to end up with poorly focused campaigns and eventual data meltdown.
Data culture
For most companies the reason they fail to keep data clean is that they have not
established an appropriate data culture. While the basic steps above are
important, data will only be kept clean if you can persuade your colleagues to
adopt a data strategy. You need to align every department and every point of
customer and prospect contact around the notion of a clean and accurate
database.
Every company needs to have one person who is responsible for the data.
However, that person ought to be supported by a culture within which data is
important. In too many companies data is seen as someone else’s job, as the
function of another, less interesting department.
Definition - data warehouse
A data warehouse is a record of a company’s historical transactional and operational
information. It enables companies to hold a large amount of non-live data in one place so
to analyse and report on that data.
You need to find a way to persuade your colleagues to treat data as one of their
most valuable business assets. Control access to it and make sure everyone
understands its worth. Create business goals and set employee objectives around
it. Whatever you do, do not allow everyone to assume it is someone else’s
responsibility, or just let it grow without an ongoing maintenance plan. It should
be treated as a key business asset at Board level.
Although data culture has to be internally owned, many companies find it useful
to bring in data experts to help them establish this culture. Good consultants can
help most companies change their mindsets and stop viewing data as a
commodity.
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Seven steps to a successful data strategy
1)
Develop a data impact model that calculates the monetary value loss
to the organisation that occurs because of poor quality data.
2)
Use it to get the attention of the Board of Directors. Their support is
critical because big changes will be on the way and investment will be
required.
3)
Convey the importance of data strategy to everyone at every level of
the organisation.
4)
Instigate a process to understand what information is required by the
organisation to support relationship marketing to both customers and
prospects. At a simple level this is likely to include a contract renewal
date and current supplier.
5)
Make sure that every customer touchpoint is aligned to collect this
information. Also make sure it is done in a consistent manner. For
example, on the website you might be asking how old the company is.
At the call centre you might asking for a date of incorporation. Such
confusion is common and involves cost and time to sort out later on.
Most of all it impedes the marketing process.
6)
Incorporate responsibility for maintaining accurate data culture within
job descriptions and performance reviews. This will keep your
colleagues focused on how important collection of data is to the
company.
7)
Review the strategy at scheduled intervals throughout the year.
Key points on maintaining data
Data will decay naturally so you need to stay constantly on top of it
Standardise data formats and processes
Use suppression files such as the Business Suppression File and Corporate
Telephone Preference Service
Use software and manual intervention to ensure addresses are accurate and
duplicates kept to a minimum
Above all, build a culture that values and protects data
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How to segment and profile your data
“I know that half my marketing works; I just don’t know which half.”
John Wanamaker, legendary retailer
Getting and keeping accurate, up-to-date data is only the beginning. Through a
combination of increased awareness and the proliferation of technology available
to help in the task, more and more marketers are achieving this basic level of data
management.
They are increasingly turning their attention to the more complex issue of
segmenting and profiling their data. This tends to follow on from the realisation
that mailing a prospect who is not interested in your product is as wasteful as
sending it to someone who changed job a year ago.
This emphasis on accurate targeting is clearly reflected in the figures from the
Direct Marketing Information Service which show that the average volume per
direct mail campaign has fallen from 176,000 in 2001, to just 91,000 in 2004.
Even those marketers who still want to mail high volumes must invest in
prioritising those prospects that seem most likely to buy from them. The
challenge for all is how to identify those most receptive prospects.
Customer segmentation
You might have millions of customers and prospects. To prioritise them and
target them with relevant offers you need to break them down into segments.
Successful database management is increasingly about creating useful
segments.
The principle behind all data segmentation is simple: work out the key features of
your best customers and extrapolate them to your prospect database. Or, to put it
another way, if you know what your best customers look like, then which of your
prospects look most like them?
To give an example, say you have a prospect database of 10,000 companies of all
sizes from all parts of the country. Do you work through them alphabetically? Do
you start with the largest? Do you start with those closest to you? If your objective
was to maximise sales revenue, you would start by modelling your existing
customers. If you found that most of your customers are food companies with
fewer than fifty employees based outside of the M25, would it not make sense to
begin by targeting prospects fitting that profile?
RFM
The first question you need to ask is: what features of your existing customers do
you want to replicate in your future ones? There are many possibilities. You might
want to get clients who pay their bills on time. You might want to get clients who
are local to you. You might want to work only for large companies. However, many
marketers begin with the RFM model.
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RFM stands for Recency, Frequency and Monetary Value. By looking at when the
last order occurred, how many orders the customer has placed with you, and the
value of those orders you can determine the propensity of that customer to buy
from you again.
To create an RFM analysis, you create categories for each attribute. For instance,
the Recency attribute might be broken into three categories: customers with
purchases within the last month, within the last year and longer than a year. You
base the size of these categories on aspects of your business; say the fact that you
produce a product upgrade every month, or you can use a statistical technique
such as CHAID to identify useful category sizes.
Depending on how many categories you choose, you create a certain number of
segments. For instance, if you have five categories for each of R, F and M, you
create 125 (5 x 5 x 5) segments. If some segments are too small you can join them
together. You can now see your most valuable customer segment: those companies
that bought most recently, most frequently and spent the most. You can also see
your least valuable segment, and everything in between. This enables you to
prioritise your marketing activity.
While RFM is a simple method that is easy for everyone to understand, it does
have its limitations. Firstly, it merely describes behaviour; it does not predict it.
Secondly, it assumes that customers will in the future continue to behave as they
have in the past. Thirdly, it may lead to excessive emphasis on the top segments,
to the detriment of other, potentially more profitable, lower segments.
Types of data
There are many different features that marketers can look at as they try to
segment their data. You will already have the transactional data that RFM uses, so
it is probably a good place to start, but most marketers combine it with aspects of
demographic data such as:
G
SIC code
G
Number of employees
G
Turnover
The principle involved is the same: if you can work out what your best customers
look like, you can begin by targeting those prospects that look most like them.
Appended data
To any company file you can append data such as detailed industry sector,
number of employees, annual sales and so on. This helps you segment your
data more clearly and so informs your marketing communications.
Consumer marketers have for some time now also used lifestyle data to segment
prospects. They classify consumers according to factors such as where they
holiday, which newspaper they read and where they do their grocery shopping.
They use this information on past purchases to predict future purchases of
different items. For instance, it might be demonstrated that people who holiday in
the UK, read the Guardian and shop in Waitrose, have a high propensity to buy a
fuel-efficient car.
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As business-to-business marketers begin to recognise that business purchases are
made by people rather than by anonymous businesses, so they are increasingly
picking up on these techniques. Furthermore, by gathering information about the
individual directors of a company, marketers are able to target the specific contact
at that company who has the greatest propensity to buy from them.
For example, Information Arts offers a product known as DNA. This uses several
sources of information on self-employed individuals to provide marketers with an
extra layer of information on small owner-managed businesses, a large industry
sector in which individual preferences figure greatly in business purchases.
Predictive models
Using appended demographic, transactional, lifestyle and behavioural data,
it is possible to create models that predict which customers are most likely
to stop buying from you, which customers are most likely to respond to a
certain message, and even which prospects are most likely to buy from you.
Doing this well can significantly improve your response rates, reduce your
marketing waste and increase your sales.
Business-to-business marketers are also beginning to look at attitudinal data for
profiling and segmentation purposes. Going even deeper than lifestyle data, this
looks at the motivation and attitudes behind making a purchase, and uses this to
predict future purchases. It goes beyond the ‘what they bought’, ‘when they bought
it’ and ‘how they bought it’, to ask ‘why they bought it’. While this is undoubtedly
very powerful data, it is also extremely expensive to gather and so, for the time
being, remains relatively rare.
Analytics are expensive, but, when used properly, 99 times out of 100 they will
pay for themselves
Key points on using data
Increasingly marketers are trying to send their marketing materials only to
those prospects who are likely to buy from them
Start by working out what your best customers look like
Then see which of your prospects most closely resemble them
You can use transactional, demographic, lifestyle and attitudinal data for this
What is data protection legislation and how to comply with it
In 1998 the UK government passed a new Data Protection Act (DPA), updating the
existing legislation from 1984. It was designed to provide a legal basis for the
privacy and protection of data of individuals in the UK, and to implement the
European Union Directive 95/46/EC. It is a serious matter for anyone involved in
the management of marketing databases and so one worthy of consideration here.
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Failure to comply with data protection legislation can result in criminal
prosecution. Do not ignore the topic and hope it will sort itself out. It won’t.
According to the provisions of the DPA, data collected by one party relating to
another party may only be used for the specific purposes for which it was
collected. Personal data may only be kept for an appropriate length of time and
must not be disclosed to other parties without the consent of the data subject.
The Act covers all personal data including names, birthday and anniversary dates,
addresses and telephone numbers.
“Before you buy marketing data from a provider, ask to see their data protection policy. If
they don’t have one, not only may they not be legally compliant, but the data they provide
could be suspect too. You need to make sure that they have obtained express authority
from the people on the list to provide that information to third parties such as you for
marketing purposes.”
Simon Halberstam, Partner and head of e-commerce law at Sprecher Grier & Halberstam
LLP, quoted in B2B Marketing magazine
The DPA is underpinned by eight data protection principles. Personal data must
be:
G
Processed fairly and lawfully
G
Obtained for specified and lawful purposes
G
Adequate, relevant and not excessive
G
Accurate and up to date
G
Not kept any longer than necessary
G
Processed in accordance with the ‘data subject’s’, the individual’s, rights
G
Reasonably securely kept
G
Not transferred to any other country without adequate protection
The main laws around the world
The UK is not the only country to have data protection laws. Around forty
countries worldwide have data protection and privacy legislation in place.
Australia and Canada have passed specific data protection legislation, while in the
US it is only relevant in certain sectors. You should always consult a legal expert
in order to understand the laws wherever you are marketing. Despite recent
attempts at harmonisation, there is even considerable variation across the EU. To
give just one example, in Germany mailing consumers is acceptable but cold
calling them is not.
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How to ensure you stay within them
The DPA in the UK has gained a reputation for being complicated and as a result
too may marketers decide to just ignore it. In so doing they are running the risk
of personal and corporate prosecution. More than that though, they are
endangering the reputation of their brand and of their profession.
We all have an interest in complying with data protection legislation
For many business people procuring the best services and products for their
company is a key part of their job description, and so they are often pleased
to hear about a relevant service or product. They welcome well-targeted
direct marketing and this is why business-to-business direct marketing
continues to thrive.
However, if those business buyers are bombarded by irrelevant material they
eventually come to see it all as junk mail. If enough businesspeople do that
then direct marketing will eventually have no impact and the profession will
die out. By complying with data protection legislation we can prevent this
from happening.
You should always gain professional advice in this area, but if you follow these six
tips you are unlikely to make any major mistakes:
1)
Gain consent to use new data for specific purposes and then only use it for
those purposes.
2)
Don’t use data in an electronic marketing campaign unless you have
complied with e-privacy regulations. These require prior opt-in in some
circumstances and opt-out in others. You should also check data against the
Corporate Telephone Preference Service.
3)
Don’t keep data for longer than is necessary to fulfil the purpose for which it
was collected.
4)
Do not provide personal data to third parties for processing on your behalf
without obtaining commitments from them that they will comply with your
processing instructions, especially in relation to disclosure and security.
5)
Before doing anything with data, think about whether you would want
someone doing the same with your data.
6)
For more on data protection, read chapters 12.1 and 12.2.
“Collect data fairly, store it professionally and use it fairly, and you will not go far wrong.”
Elizabeth France, the UK’s first Information Commissioner
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Summary of data protection legislation
Data protection is a serious matter for anyone managing a database
In the UK you can only use information for the purpose for which it was
gathered
You must not disclose data to anyone else without the specific consent of the
subject
Data laws around the world vary and so it is always advisable to gain expert
legal advice
Complying with data protection legislation should not be just a matter of
avoiding prosecution; it is essential if we are to maintain the legitimacy of the
direct marketing profession
FedEx
The business
Headquartered in Memphis, Tennessee, FedEx is a network of companies
spread across 220 countries. It employs a quarter of a million staff and
every day it delivers around 3.3 million packages. It runs 674 aircraft, the
world’s second-largest fleet, and has more than 70,000 other vehicles. It is
also renowned for its website which allows its customers to track their
packages during every stage of the journey.
The challenge
In 2002 the MD of marketing for northern Europe, Jeremy Twait, was
reviewing the company’s marketing plans in the UK. Facing some tough
growth targets he was weighing up the strategic issues, such as the
location of depots and the targeting of marketing and sales materials.
Those growth targets had been based purely on the UK’s Gross Domestic
Product (GDP). FedEx head office had seen that the UK has a large GDP
and so assumed from that that there must be a significant demand for
international courier services. Twait realised that he needed to get a
clearer picture both of what the actual level of demand was, and where it
was located.
Concurrently, Jeremy Elder, Marketing Communications Manager for
northern Europe had realised that the company was facing a major issue
in its data collection.
He says: “We were purchasing thousands of company names, selecting
them using SIC codes and size, and then using a telemarketing bureau to
find out whether or not they had a need for international courier services.
Only ten per cent of them did, meaning that the work to date on ninety per
cent of the leads was entirely wasted. Given that the data cost around
£250 per thousand, and the telemarketing considerably more, this was a
significant waste of resources.”
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Chapter 4.3 : Managing and using the B2B database (ensuring data quality and cost)
The solution
FedEx hired Information Arts to tackle these problems and the company
rapidly recognised that the two problems were aspects of the same issue.
Essentially FedEx needed to find out the true level and location of demand
for its services in the UK.
The consultancy developed a Market Demand Model (MDM) for FedEx,
using two years of transactional data from FedEx customers, combined
with Information Arts’ proprietary software, Geodemographic Industrial
Classification (GIC). In simple terms, GIC enables users to map prospects
by location.
The MDM provided the foundation of FedEx’s first UK prospect database.
Elder comments: “In the past we’d used a US system, which wouldn’t hold
address records in a format that was compatible with the UK postal
service. In fact we were unable to deliver to around 25 per cent of the
companies on it. So, every time we used it we had to pull it out, clean it
and move it to a local database. Having our own UK database was an
immediate advantage, as was the addition by Information Arts of a unique
reference number to each record. That eliminated all the duplication on
our database.”
However, the most important outcome was that FedEx could now assess
the true level of demand at a local level. Simon Lawrence, MD of
Information Arts says: “We could see the level of demand by postcode, so
when we added it all together we had the total market size for FedEx in
the UK. We compared it to a report on the subject by MarketMonitor and
found that we were within five percent of each other. Our results also had
the crucial difference that FedEx could break them down by postcode.”
FedEx was left with 75,000 companies to target. This was a much smaller
prospect universe than it had previously estimated and so enabled the
company to deliver its marketing communications in a much more focused
way. Elder reports: “If we think they are a potentially big account then we
can arrange a site visit for a field representative straight away, where
previously they might have had a telesales call once a quarter.”
Initially it drip-fed the leads into the sales team and adjusted the model
based on the feedback from this. Eventually, in August 2003 it was used
in a full- scale marketing campaign for the first time.
The results
FedEx now finds that 68 per cent of the leads it buys have a need for
international courier services, a remarkable increase from ten per cent.
Lawrence explains the benefits this has brought the business: “First of all
FedEx has been able to dispense with the services of the telemarketing
bureau, saving it a great deal of money. Secondly it spends less on the
raw data, since it needs to buy less of it to achieve the same result.
Thirdly, the sales pipeline has contracted. While it used to take a long
time for leads to be qualified, they can now be contacted immediately and
revenue generated more rapidly. Finally, this has really improved the
confidence and so the performance of the sales team.”
He goes on to note that for the year between May 2004 and April 2005,
FedEx in the UK was facing very tough sales targets. It was this that led
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Chapter 4.3 : Managing and using the B2B database (ensuring data quality and cost)
Twait to review the approach to marketing in the first place. Partly as a
result of the database management the company did in the run-up to this
period, it was able to meet its target by November 2004, less than halfway
through the year.
The methodology has been so successful that FedEx has rolled it out to
other countries in Europe, and has also applied it to its courier route
planning and its sales performance management.
Fiat Commercial Vehicles
The business
Fiat Commercial Vehicles manufactures light commercial vans. From the
large Ducato and Scudo, to the high-powered Doblò Cargo and the lowcost Punto Van it has a range of vehicles, and it markets them entirely
separately from its consumer cars.
The challenge
The company wanted to find out more about its customers. They are all
small businesses that use vans, but beyond that Fiat lacked data that
would help it target its direct marketing and so improve renewals and
drive sales among new prospects. For some time it had been including
questionnaires in its quarterly newsletters to its customers, but the
response rate had not been good enough and in 2003 the company
decided to do something about it.
The solution
It hired direct marketing agency Crazy Horse and business-to-business
database marketing experts, Information Arts. The latter began using its
proprietary DNA product to find out more information about the
individuals responsible for vehicle purchases among Fiat’s database.
DNA was designed to aid the targeting of small businesses. It profiles the
business buyer by his or her home address and so applies
geodemographic information. It also uses lifestyle information about the
buyer, such as newspaper choices, car purchases, holiday destinations
and family composition.
Information Arts applied DNA to around 10,000 Fiat customers. These
were businesses ranging from the ‘white van man’, a self-employed
tradesman, with his own van, up to larger companies with a fleet of four
or five vans.
It segmented the database by the profiles of the actual people making the
buying decisions, and crucially it also included businesses that are not
captured as businesses by BT’s OSIS.
The results
This work not only significantly improved Fiat’s targeting, it also had an
unexpected side benefit. Information Arts discovered that there is a high
correlation between business people who buy Fiat vans for their company
and people who drive Fiat cars.
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Chapter 4.3 : Managing and using the B2B database (ensuring data quality and cost)
This suggested that they were loyal to either the brand or to their dealers,
and so offered an interesting new avenue for Fiat’s future marketing
activity.
The ten key learning points from this chapter
1)
Effective targeting of direct marketing takes more than good database
software; it requires good database management.
2)
The process of building a database should begin with collating and
organising what you already have.
3)
There are three main sources of prospect data: compiled data,
Companies House data and subscriber lists.
4)
The cheapest list is not always the best value. It is vital to consider
return on investment.
5)
B2B data decays rapidly and so you must invest time and money into
the maintenance of your data or it will rapidly become obsolete.
6)
Suppression files and data cleaning software are important but the
key element in data maintenance is the establishment of a culture that
treats data as a precious commodity rather than as someone else’s
tedious task.
7)
Successful segmentation and profiling can help a marketer reduce
costs, increase response rates and prioritise leads.
8)
You should begin by working out what your best customers look like
and then find out which of your prospects look most like them.
9)
You can use a combination of transactional, demographic, lifestyle and
attitudinal data to describe these profiles.
10)
Data protection legislation is important for all database marketers,
because failure to comply can result in prosecution, and can also be
highly damaging to how buyers view direct marketing.
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