In "Marketing Management", Philip Kotler describes database marketing as
"...the process of building, maintaining, and using customer databases
and other databases (products, suppliers, resellers) for the purpose of contacting and transacting".
Wikipedia describes it as
"...a form of direct marketing using databases of customers or potential customers to generate personalized communications in order to promote a product or service for marketing purposes".^Top
The basic steps of database marketing are:
prepare the data - find the patterns - make the predictions.
In reality, there are many more
steps involved in the cycle; capturing and understanding requirements, collecting the data, training the models, testing the hypothesis, and feeding
the output back into the business - which may in turn alter the requriements. Database markting is an itertative process, as a result of the dynamic
nature of business data.
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PatternSoft ltd are a Database Marketing Services provider, aimed at
supplying data quality and business intelligence services to small and medium sized businesses in the UK.
We provide a full range of database services, usually only available to large enterprises, but do so in an accessible way that is aligned
to the needs of our clients and their data.
Our staff have a background in several vertical markets, including finacials, public and service-based sectors, working for a variety of
different blue-chip clients. We have worked on 1-to-1 Marketing, Direct Mail, Loyalty, Analytics & Dashboards, BI/MI reporting
and data management projects. We also have practical understanding of information security, knowledge management and information
aggregation & collaboration systems.
We are located in the East Midlands.
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We believe we are uniquely placed to provide a level of data management and insight not previously accessible to lower volume data owners.
By providing a scalable set of services that are tuned to the data availibility and analytical understanding of smaller companies, we can help SMB's
to achieve their first steps on the road to full-cycle data insight.
PatternSoft is happy to provide assistance at each step to ensure our clients understand how
the services work, what the services do, how best to use the outputs and ultimately, how to turn it all into business results.
PatternSoft - supporting smaller companies with bigger ideas.
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Address cleansing involves verifying or fixing address data in files, so that it matches the Post Office's reference to the address.
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If your addresses are wrong, you can't communicate with your customers effectively. Worse, you are losing money through undeliverable mail, every time you send out a mailing.
Additionally, the Data Protection Act states that your data must be up-to-date and relevant at all times.
Address Cleansing forms the backbone of compliance with this particular ruling.
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What can be said for Addresses is also true for Names.
Names should be kept up-to-date, to ensure compliance, as well as to ensure a professional, customer-centric approach to communicating with customers.
PatternSoft can expand names from initials, and also verify whether a name is known at an address or not.
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Address cleansing uses Royal Mail supplied files to match addresses against.
The primary file is the Postal Addresses File, (the PAF), but there are others, such as the Postcode information File, (the PIF), which is used to derive DPS codes, (see below). Names validation uses the Electoral-Roll, the register used to store the names and addresses of all UK voters.
PatternSoft uses an enhanced version of the Electoral-Roll that is integrated directly into our Address Cleansing service, which means name and addresses are validated against more than one source, ensuring maximum accuracy.
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Every discrete address in the UK has a DPS, or Delivery Point Suffix.
The DPS is used internally in the Royal Mail to allow a machine-recognisable version of the address to be made, which turn allows for automated processing of mail.
To encourage use of DPS's, the Royal Mail provides discounts for Bulk Mail that uses these codes, (see below).
Generally, DPS codes are expressed as CBC's, or Customer Bar Codes.
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Ideally, data should be cleaned on a recurring, regular cycle.
This ensures your company data is compliant, and also reduces the cost of managing, and ultimately, owning the data.
At worst, it should be done before any major data activity.
Data should be as clean as possible to maximise matches with other data quality activities, such as suppression, enhancement, analysis, MailSorts, etc.
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Data suppression involves removing from customer files those contacts that are, for some reason, no longer reachable.
Generally, this is down to people moving house, but can also be a result of bereavements, or even just people choosing to "opt-out" of certain channels of communication.
Suppression comes in many forms, is often supplied using many different files, and prices inevitably vary wildly between products. Some suppression files are perceived as better than others, depending on how you define "gone away", deceased and do-not-mail.
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PatternSoft holds suppression files for address-based files, removing "gone aways", deceased and do-not-Mails.
We do this as a single unified service, for which there are only two prices, regardless of the suppression files used; One for traditional suppression, where records are removed from the output, and one for flagging, where the record is not removed, but instead flagged as suppressed.
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For mail-based communications, there's no legal requirement to suppress data, although it could be argued that deceased customers should be removed on a regular basis.
Members of the DMA, or Direct Marketing Association, are obliged to screen against the MPS, or Mailing Preference Service file, the UK's official mail "opt-out" file.
For telephone and fax communications, all marketing phone calls must be screened against either the TPS, (the Telephone Preference Service file), the cTPS, (the business/corporate number version of the TPS), or the FPS, (the fax number version).
Not doing so can result in a fine of up to
£5000 per call.
There is also an official email address file for screening, but this is little used, as the legislation around email and other digital communications is different to that for mail and phone, in that it is far more "permission-based", (a company must have explicit permission before mailing, or the recipient must be a previous customer).
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It's not usually good, but in the context of suppression, it's actually a positive thing.
By removing customers known to be unresponsive or unreachable, companies can reduce their communication costs, whilst increasing their response rates.
Why waste money mailing, faxing or phoning a customer who isn't there?
Also, not all "gone away" customers are really gone - they can be tracked using our Address Tracking service, (see below).
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PatternSoft first ensures that the input file, (your customer address file), is clean, well-formatted and de-duplicated.
Following this, the file is screened against our Suppression files, and any suppressible records are counted up.
A report is produced, allowing us to give you a breakdown of counts and costs, and allowing you to choose whether to accept the costs and continue with processing the file.
Only a nominal processing fee (per 1000 records) is charged, if, at this stage, you choose not to continue. Otherwise, there is a charge, based on suppression or flagging, that is applied per record affected.
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As part of the suppression output report, records that have been marked as "gone away", but that have a forwarding address available, are marked separately.
By paying the Permanent Flag charge for the record, you can have this new address appended to your record.
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Address tracking uses information sourced from a collection of files from The Royal Mail, along with various contributions from companies and organisations.
Whenever a consumer informs a public or private body that they have moved, there is a good chance that their forwarding details will be added to one of the house mover files.
This is then linked back to the customers last known address, forming a history of addresses.
For some consumers, this can be fairly long, meaning even if your records are particularly old, there is still a chance a current address exists for your old one.
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Data should ideally be screened for deceased customers on a regular basis, depending on the nature of the business.
More general screening should be done prior to any major data activity, such as suppression, enhancement, analysis, MailSorts, etc.
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De-dupe, merge/purge or de-duplication is the act of taking records that signify the same entity, (be it a person, a family or a household) and combining, deleting or extracting them to create a single reference.
As files and databases grow, the chance of replicating data increases.
The same row may be entered several times under slightly different guises, such as "J Smith", "John Smith", "Jon Smith", "Jay Smith", etc.
Each may in fact be the same individual, but because of the duplication, you may be sending several copies of the same mailing to them.
This increases the likeliness of their annoyance at the intrusion, and your costs, both unnecessarily.
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Formatting allows data that has been poorly stored to be re-structured, properly-cased, correctly-aligned and generally made easier to work with.
Several options are possible with our formatting tools, including deriving proper salutations, proper name grammar, correct casing of address elements, etc.
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For large mailings, the Royal Mail offers a variety of different discount schemes to drive your postage costs down, whilst minimising the work for them.
All of these schemes are related in that they require specific sort algorithms to be applied to mailings before delivery to the sorting office.
Generally, these schemes require that data and outgoing mail be sorted to various postcode and DPS, (see above) resolutions, which identify the responsible sorting office for delivery, or for the highest discounts, the actual "walk" that the postie takes.
In addition, further savings can be made by using a CBC, or Customer Bar Code.
These are printed, machine-recognisable stripes applied to the mailing at the same time as the sorting. The CBC is derived from the DPS and the postcode.
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Most operational systems only collect the barest information about a customer, as they are generally product focussed - name and address usually, maybe some other contact details, maybe gender, maybe date of birth.
But a customer represents more than this; their income, family size, car ownership, tenancy status and more can all contribute to the decisions they make, and ultimately, whether they'll buy your goods or services.
By enhancing data with additional attributes, companies can gain a higher resolution view of their customers and behaviours.
Data enhancement can generally be applied at postcode sector, household and individual levels.
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The choice of attributes is enormous, but the final configuration comes down to what patterns you're looking for in your data.
Enhancement data is usually either demographic and attitudinal in nature.
Demographics relate to the properties of the individual, such as age, nationality, income, etc, whereas attitudinal data relates to behaviour and opinion.
Demographic data is generally easier to get hold of.
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Appending attributes in itself is only really useful to "fill the gaps" in data you may already hold. In combination with analysis though, attributes can lead to an in-depth understanding of your company, its customers and the market you operate in.
Identifying patterns in your data can be difficult if only very few details are known about factors that may influence, for example buying patterns, or response rates. By increasing the "surface" of the data, the likelihood of patterns emerging increases, allowing correlations between groups of customers or their habits.
Rather than marketing one way to all customers, you can begin to market to groups of customers, based on their needs and buying patterns.
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Like data enhancement, geo-coding involves expanding datasets out to make pattern identification easier, but this time, the attributes are physical, map-based locations.
Geo-coding takes addresses or postcodes, and returns a latitude and longitude for the addressed location.
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Geo-coding has a great number of uses, but those most interesting to marketers are spatial analysis and geo-functionality, (such as "Where's the nearest..." or "How do I get to...").
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If you run a business that is geo-sensitive, then understanding the layout of your network, your customers, and your competitors can be crucial.
Geo-coding allows you to target offers to localities with heavy competition, discover where to build new sites or maybe just help customers that move to find their nearest new store with detailed maps on "movers packs".
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Analytics, or more generally, data mining, represents a statistical-centric data appraisal to identify any rules or patterns that may exist in historical data.
It is the identification of probabilities, rather than certainties.
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By "training" statistically-derived models, it's possible to achieve a degree of prediction scoring against various business scenarios.
Depending on the nature of the type of scenario under investigation, various algorithms are applied to the data to detect and predict the patterns and rules that dictate the inter-relations of the data.
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The kinds of investigation that analytics is well suited to includes:
How will raising prices impact customer churn rates?
What are the key influencers of whether a customer will buy product X?
Which journeys through a website tend to lead to purchases?
Which customers are most likely to respond to promotion X?
The only real limits are imagination and the necessary data.
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It can sometimes seem so - companies can often be surprised at the treasures their data holds, but no; it's just maths.
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It can be - analytics tends to be an investigative, iterative process, with a reasonable amount of close contact between the analytics team and the client.
The scenarios under investigation and the nature of the data tend to dictate the time-span (and thus the cost) of an analytics job.
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Mailing lists are databases of consumer and/or business contact details.
They are usually rented from list suppliers or owners.
In general, they have a usage license associated with them, as well as fees levied at the row level, (e.g. £100 per 1000 rows). They can be rented on a one-time basis, or leased over a longer period, (usually 12 months).
Lists are usually business-to-business (B2B) or business-to-consumer (B2C) oriented, although there are exceptions to this rule.
Generally, B2C lists require you to register your marketing material with the list owner, so they can ensure it's an acceptable use of their data. This is generally a fairly painless exercise, and is done to comply with Data Protection legislation and industry best practice.
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Generally, they're compiled via a proprietary databases owned by data-rich companies, such as a mail-order retailers, business associations, utility companies, magazine publishers, catalogues retailers, customer databases where consumers have opted in for 3rd-party communications, public data-sources, etc.
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The benefits of mailing lists include the ability to rent customer details that suit your business, (although the exact criteria available to choose from can vary between files), as well as being able to select from lists of customers already likely to have a propensity to buy your products or services.
For example, prospects that match your customer profile and subscribe to a holiday magazine have a higher probability of buying an all-year-round holiday insurance than customers who aren't so focussed on holidaying, even if they do match your profile.
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Definitely not.
There are two main types of list, (other than B2B and B2C) - niche lists and generalised lists.
Niche lists represent smaller, but tightly focussed lists of contacts that tend to share an interest, characteristic or habit. Generalised lists are attempts to represent "consumer universes", and often contain millions of rows.
Magazine subscriptions and 3rd-party opt-in lists are examples of niche lists; Utility company lists and lists derived from the Electoral-Roll or similar national registers are examples of generalised lists.
Another important aspect of lists are their "freshness", and whether they represent prospects, or customers.
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A prospect is a contact who is unknown to the list supplier or owner.
They have simply had their details collected at some point, but the list suppliers have no idea of their propensity to buy products or services.
Customers, somewhat unsurprisingly, are contacts known to have purchased goods or services, and generally have a level of purchase history associated with them.
Customers are (usually) more valuable than prospects.
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No.
Contacts are protected by Data Protection Legislation, not to mention the copyright of the phone book owner.
This is true for most data-sets not explicitly licensed for marketing use.
However, publically available data does exist, such as the (Edited) Electoral-Roll.
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If rented from a reputable supplier, yes.
When sourced properly, the lists are usually up-to-date in terms of TPS, MPS and FPS screening, and are usually in pretty good shape address-wise.
Always ensure that you understand the origin of a list, and it's licensed usages.
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Price depends on the quality of the list, the type of license, the supplier, the market represented and a host of other factors.
It's possible to pay a penny a contact, but you tend to get what you pay for - cheap lists tend to be over-used.
At the other end of the spectrum, it's quite plausible to pay several pounds per contact, but 15-50p probably represents a reasonable average for the generalised lists.
Niche lists can often cost more.
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No, lists will often be seeded with "honey-pot" contacts that are actually endpoints of the list supplier, and these are used to identify license infringement.
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In a data context,
PatternSoft defines Small Business as those with less than 10,000 records of customer data.
Medium businesses are those with less than 100,000 records, and enterprises represent the largest customer data owners.
Small businesses have a different set of services available to them.
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Primarily, because they have less data, but also because their budgets tend to be more restrictive.
PatternSoft takes the view that, rather than simply abandon the idea of database services for low volume/low value data owners, a separate approach needs to be taken to at least ensure that these companies can achieve the "low-hanging fruit" possible through a cohesive data strategy.
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We've tried to ensure that all our services are useful to small businesses or low volume data owners.
There is a lower limit of course, (if you've only got 10 customers, then there's not a lot you can't achieve with a pencil and a rubber that our cleanse and suppression services could supply).
In general, there needs to be some volume of data for our services to be worthwhile. This doesn't always need to be customer data - transactional data is also useful for analytics, (necessary even for some computations and predictions), and can sometimes make analytics possible even when there are fewer customers than are usually required.
If there's enough customer data for us to create a customer profile, then it's always possible to source some prospect lists to investigate, extracting customers that suit your business needs, (see above).
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Mainly because they won't be treated indifferently.
PatternSoft recognises that the low volume data owners of today are the data behemoths of tomorrow.
By offering a set of data hygiene, purchasing and analytical services tailored to SMB's, combined with a marketing knowledge that spans several vertical industries and practices, we believe that
PatternSoft are uniquely placed to catalyse the use of sophisticated marketing in the Small Business arena.
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We can process your files in almost any format; we can happily handle CSV, TSV, Excel, Access databases, dbf files, fixed-width files, XML data, etc. We try to provide outputs in an equivilant format, where possible.
Contact us with your requirements so we can verify the file formats.
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We can produce formats as Excel workbooks or PDF files. We can also supply raw data summaries for data quality processes.
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When validating and fixing addresses,
PatternSoft will apply a score to each result.
This score will indicate a variety of potential cleanse, verify and fix actions, but in essence, all addresses will either be Pass, Tentative or Fail.
Pass and fail are fairly obvious, but tentative needs some explanation. Basically, if a reasonable score was achieved, but the input data deviated in certain key areas from the output data, then a Tentative score is applied.
In general, it's worth investigating these matches, as often, they can be salvaged with a little manual intervention, (and the score often indicates where the problem lies).
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In the UK, all data processing and management is legislated through the Data Protection Act. This act stipulates a set of rules that must
be confromed to, all of which aim to provide a framework for ensuring privacy of the individual and best practice data management processes for businesses and organisations.
It legislates, amongst other things, that data collection and storage must only occur with the prior knowledge and permission of the subject. In addtion, it states that any data retained
must be used for a relevant purpose, and kept up-to-data and correct. It must also be kept secure.
Data should be also accessible to the subject, so they can check for relevance, and request corrections.
Check our
resources page for links and further information.
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These regulations specifically relate to your electronic communications, such as email and telephone marketing. In essence, it requires you
to clearly identify yourself on all communications. Check our
resources page for links and further information.
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Data security is a complex subject, ranging from physical security to process mapping. It's improtant to consider how data flows through your company, and where the points of failure are.
A succesful information security framework will assess who has access to data, which data is most sensitive, where data goes and how long data lives. By impelmenting techniques such as identity management, encryption,
business process engineering and data auditing, the environment in which data exists can be secured.
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PatternSoft can provide 1-to-1 services to SMB's to assess the current data environment, the problems and issues surrounding the environment and possible solutions.
Contact us now with your requirements.
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