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Specify Business Marketing Data

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Specify the right business marketing data for your next initiative.

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b2b data uses: Email vs Postal Campaigns

Email Marketing vs Direct Mail

Whilst email marketing has its place and benefits, the overall return on investment is considerably lower than most would perceive. The initial cost of an email database needs to be factored in, and compared to the percentage of responders and eventual conversions to becoming a new customer.

The truth is that many email broadcast messages are deleted without being read. The reason being that most of us see an email (from a company we have never heard of) and delete it immediately. Not just because we don’t know who the sender is, but the threat of viruses also makes us wary.

One of the main perception challenges is that many businesses stay in touch with their customers via email, typically through a monthly bulletin or service update, and these messages tend to generate a healthy response rate. Typically 1% – 2%, or even higher. But in contacting a new prospect cold (i.e., for the first time) there is no existing relationship or awareness, so the response rates are typically between one per 1,000 emails and one per 10,000!

Sourcing 10,000 email addresses is not cheap. At least it’s not cheap to source 10,000 email addresses from a reputable b2b data list broker. The reason being that the more reputable business data sources invest manual resource into telephone verifying the email addresses within their file. And that costs. These costs are reflected in the overall price of the data list. So it would not be unreasonable to expect (for example) five responses from 10,000 email addresses.

By contrast, direct mail (i.e., postal mailings) are still generating the same average response of around 1%. So instead of five responders from a mailing of 10,000 emails, a postal mailing of the same volume can typically expect to enjoy 100 responders. Twenty times as many.

Yes there is the added cost associated with printing, packing, posting and the stationery. But does this make it all cost prohibitive? Not necessarily: for postal mailings in excess of 4,000 units a reduced postal rate (Mailsort) can be enjoyed. And by using a mailing house, letters can be machine-printed and machine-packed too.

Over the last few years Responsiva have conducted many email and postal mailing campaigns. Well in excess of 100,000 units for each initiative. The postal mailing route comes out on top every time. The postal route typically costs in the region of 40p per unit (all inclusive), rendering the average cost per enquiry in the region of £35. And yet email marketing (because of the much lower response rates) tended to come in at hundreds of pounds per responder. The truth is that the results and return were not even close.

Whilst this is not to say that email marketing should not be adopted, there is an element of “horses for courses”; any business with a particularly high sale value (say £10,000+) should do well from email marketing. For example; vehicle sales, corporate IT systems or any service which has a proven lifetime value totalling five figures. But if your typical sale value is just a few hundred pounds (or lifetime value around £1,000 per customer) then it is more likely that the postal mailing route will yield a higher return.

Postal mailings may sound ‘expensive’, but an investment cost is all relative to the return. And postal mailings do have a considerably higher return in terms of the percentages. Being frightened off by the costs of postage, or being lured by the “cheap” cost to run an email broadcast, is a false economy. Long gone are the days where every email would be opened, or that recipients would think “yippee, I have got an email: let’s see what it says”. In this day and age, most new emails are ignored and deleted without being read, or are even filtered to the spam box without the recipient even seeing the headline.

Consider postal mailing activity carefully. 500 – 1,000 letters is a good starting point for a trial. The business data list should not be expensive, and all employees should help out with the printing and packing. It won’t take long to complete.  Measure the responses; both in terms of volume and quality. And if it yields a reasonable return, evaluate the time and cost savings by ramping up the campaign roll-out to 4,000 units or more. A mailing house can manage the printing and packing at a very good rate, and the postage discounts are considerable.

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B2B Data Specification

B2B Data Specification

 

Prospect data specifications can be ambiguous, so it is imperative to ensure they are accurate. In my opinion, it is the responsibility of the list broker to discuss the b2b data requirements with the customer and then take ownership of specifying the required data list in accordance with the customer’s requirements. It would then be the customer’s responsibility to agree to that specification, or make changes where required.

This goes back to my previous point:

 

  • The marketing manager (data purchaser) needs to say what they want

 

And

 

  • The data supplier (list broker) needs to ask questions

 

Having worked within the marketing data industry since the 1980’s I have seen many examples of errors, which go some way to justifying why (a) customers need to work with a fully trained and competent account manager and (b) why it is always best to source data from a data ‘person’ (i.e., with open discussion) rather than from an automated / online data purchasing download system.

Typical examples include;

 

  1. A.    The Nurseries

A client who sold children’s soft-play equipment wanted to target nurseries. He was supplied a data list, roughly equally split between the industry classifications “nurseries & crèches” and “garden centres and nurseries”. The problem was quickly spotted and rectified, though it is perhaps easy to understand why this issue occurred in the first place. But many automated downloading systems request advance payment before you download the data list. So a refund is not always granted once you press “buy”, because data is essentially ‘information’ and once you have been given the information it is impossible to return it. Furthermore, some of the online ordering systems may appear user-friendly at the front end, but it is not always easy to get through to a person on the telephone (and get refunded) if an error such as this has happened.

 

  1. B.     SME’s

One of my favourites is an appreciation for what constitutes an SME (Small to Medium Enterprise). If a client ever says to me that they wish to target SME’s, I always respond by asking what they mean by this. This is coupled with a suggestion, such as “would 5 – 100 employees be acceptable?”. Nearly always the client would come back to me with an alternative employee band, or turnover figures. And despite nearly twenty five years of data experience, my guess at what the client thinks an SME should be differs from their reality.

Responses such as “No, there needs to be at least 50 employees. Say up to 1,000” are commonplace. Or “Sole traders are fine, so anything up to 50 employees will do”.

Both of these responses not only make a huge difference to the data available to that brief, but will also have a considerable impact on the marketing initiative’s results.

 

Back to the earlier point; the marketing manager said what they want (“SME’s”), and the list broker had to ask a question to clarify exactly what that meant. It’s not difficult!

 

 

The important thing to remember when selecting data is that the fields are usually gathered and verified by telephone. This creates possible anomalies for numerous reasons;

 

  • Changes to the company data over a period of time (since the last update)
  • Data capture keying errors on the part of the data verification company
  • Exaggerations or errors on the part of the company being verified (data can only be updated on the strength of what is advised)

So if a customer requires companies with 5 – 100 employees, consider that the companies with precisely 5 employees (and there are approximately 200,000 of them!) could for example be a husband & wife partnership, with two or three temps. When they were last called (and the employee size verified) they may round up to saying there are five employees, in the interest of giving a simple number or “bigging themselves up” a little.

 

  1. C.    London

What is “London”?

The City of Westminster? The square mile? The postcodes EC & WC? An area within the North-South Circular? The compass-point postcodes (N, E, SW, W etc)? Or is it the area within the M25?

The reason I ask it this way is because customers frequently have a different view on what constitutes the London area. Typically I would suggest the M25 area to be correct, but I never assume this and always clarify with the customer first. This is all part of the specification process, and back once again to asking questions to clarify the true requirements.

 

An Example Specification

The b2b data specification needs to cover all bases, and accurately clarify what the client needs. Here is an example;

  • London (postcodes WC & EC only)
  • 10 – 50 employees
  • All records must include a director or business owner (no managers / branch managers)
  • All records must have a TPS-checked telephone number
  • Exclude charities, government, medical and education sectors
  • Exclude national chains (companies with 10+ branches)
  • Select OFFICE premises only
  • Select only companies with an accompanying email address; exclude generic email addresses (“info@” etc)
  • Then: select and supply the 1,000 most recently verified records

This brief covers all bases and by operating to this same standard client complaints after the data is supplied are extremely rare.

 

Control Cells

A control cell is a selection of the data which is used to test the campaign results. For example; if your target market is accountants with 5+ employees, the eventual data selection (of 1,000 records) may be as follows:

  • Accountants with 5+ employees :        900 records
  • Accountants with <5 employees:         100 records

Although the latter selection is not within the desired brief, this 10% of the file acts as a sense-checker. When the campaign has finished, and the results are reviewed, ask the question: did that 10% (the control cell) yield a similar percentage of enquiries / responses / sales?

Although in many cases control cells do not yield as well as the main selection, occasionally they do throw up pleasant surprises. One possible example is that larger businesses tend to prove harder to reach the business owner through a telemarketing campaign, whereas the smaller companies (with less than 5 employees) can yield a greater connection ratio to the business owner. For this reason alone, the smaller companies may prove more fruitful. The sale potential may be smaller, but with the increased connectivity the overall sales may prove higher.

Always consider a control cell, even if your ultimate conclusion is not to have one.

 

Request Samples

In addition to providing a data specification, good data list brokers will also supply a few samples. So if you aren’t supplied some as standard, then request some. These samples are not intended for use in a test campaign, though they can be. Their main purpose is to illustrate how the data is supplied, the fields and format of the data supply and (most importantly) for the customer to sense-check that what is being supplied meets with their requirements.

For example, the client may respond to the brief & samples with “I see the samples contain an estate agent; actually, we don’t want those either”.

 

Request A Breakdown

The client has the right to say “I need to sense-check the full 500 records you are proposing to send me, so please would you email me an industry classification breakdown?”.

Or; “Can you email me a postcode breakdown?”

What this will achieve is to let the client see the kinds of business (or their geographical spread) that will comprise their new data list. How many accountants, solicitors, graphic designers etc, and where these businesses are located. And from this they can pick out any additional undesirables to ensure their eventual list is exactly what they need.

 

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Customer Survey Proves B2B Data Quality Is Paramount

20110223 Sital Responsiva video

Responsiva’s regular customer satisfaction surveys consistently prove that b2b data quality is the paramount consideration. Whilst pricing is always key, minimising the number of mailing returns or dead phone numbers and ensuring the business data targets are exactly right for the client target market are of considerably higher importance.

This short video from Sital gives an overview of the statistics from Responsiva’s customer satisfaction surveys. Over the years these figures have altered very little, and even in times of recession the business data quality remains the highest priority.

More than 70% of Responsiva’s prospect data orders now come from repeat customers, who have previously experienced the exceptionally high attention to detail and data accuracy provided by us.

For more information contact Responsiva on 0800 118 5000 or email us at info@responsiva.biz

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The Cobbler’s Shoes And b2b data

You may have heard the story of the cobbler, whose kids were clothed in worn-out shoes? The point being to ask whether you would buy shoes from such a trader? Or would you go to the dentist who has manky teeth? I am often approached by mailing houses, offering to print, pack & post Responsiva’s monthly postal mailings; but when I ask them what mailing activity they run they explain that all their new business comes from word of mouth. Or the business coach who offers to help me make my business run without me, whose own business couldn’t run without them. Or even from telemarketing companies who generate new business from networking events or email marketing, rather than by picking up the phone.

No matter what your line of work, if you offer a product or service then you are best placed to take the benefit from it; you can ensure you receive the best possible service, and at cost price too. So with all these benefits, if you cannot sell your service to yourself then ask yourself what kind of service it is you are offering?

As an experienced b2b data list broker, Responsiva supplies business lists for postal mailings and telephone marketing. And with that we send out a postal mailing to new prospects most months. And not just because of any support in our own service, but more importantly because it yields a healthy return on investment. Response rates are typically around 1% – 1.5%, and up to one quarter of those responders ultimately convert to becoming a new customer. The ratios (measured over four years) have proven that for every £1 spent on postal mailings have delivered approximately £2.50 in profit from new business sales. That’s not revenue; for this the ratio is obviously higher. This is quite simply a straightforward 5:2 return on investment ratio from sending out a regular business mailing to new prospects most months. Although Responsiva obviously sources the b2b data list at cost price, the truth is that the mailing list is supplied for multiple usage. So many of the business prospects are re-mailed a few times, making the cost of the data list considerably more efficient. But this does raise the question as to whether a re-mailed business is more or less likely to respond? Responsiva’s statistics on this subject go back more than ten years, and is an area of both interest and focus. If you mailed 1,000 prospects for he first time, are they more or less likely to respond than if you had already mailed them one or two months ago? And are these any more or less responsive than business prospects you had mailed six times over the last one or two years?

The reality is quite straightforward and well worth remembering. The results are the same; a prospect is just as likely to respond if you have mailed them previously (though our measurements only go up to six times) than if you are touching them for the first time. That said, you must remove all mailing returns and responders from any future mailings, which will typically comprise around 3% of the mailing list.

All companies should have around ten channels to deliver new business enquiries, and postal mailings have proven to be a consistent route to market. And the postage is not so expensive when running campaigns of 4,000 units or more, due to the Mailsort discounts which are applied. And if you are thinking “but we could never run 4,000 postal letters every month; we are just a really small business. We couldn’t afford it and couldn’t cope with the volume of responses” then consider this fact: Responsiva is operated by just one person. You can never have too many new business enquiries; it is just a case of how you manage them.

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White Collar Business Data List

The most common approach for companies who seek a business data list of white collar workers is to review the industry classifications. With around five hundred SIC codes, and two thousand lower level business data descriptions, these will show the vertical market that each company operates within. But does this method truly identify the white collar workers from the blue? Can you be sure that accountants and solicitors are the former, and manufacturers the latter? Imagine two scenarios

Company 1: ABC Solicitors

This firm has ten branches; they are a large firm of solicitors. Nine of their offices are located in major cities. The tenth branch however is the only premise that is located within your desired catchment area, so it is this site that would be picked up by the data. Unlike the other nine sites, this branch is a warehouse premise, where all secure documents are stored. Aside from a general manager, all employees are dedicated to the warehousing and storage functionality of the business. Is this the kind of operation you would want to target for white collar related services?

Company 2: LMN Manufacturing

Similar to our firm of solicitors, this manufacturing company has ten premises and just one of these premises resides within the locality of your target region. The other nine sites are factory premises, manufacturing goods in line with the company’s product range. But the tenth site is the head office premise, where the functions of finance, sales, marketing and account management reside. So in this case we have a white collar operation, despite the overall nature of the company being predominantly blue collar.

These examples are quite extreme, but go to illustrate the point that the industry classification of a company is not necessarily indicative of the functionality of the premise being targeted. And so for this reason, there is a second variable which requires consideration; the business premise code. A warehouse or factory premise is ideal for marketing to for services such as industrial waste disposal, blue collar related training services etc. Whereas these premise types should be excluded if marketing into white collar service companies.

Based on the fact that these examples are quite extreme (the first being more so than the second), as a general rule the industry classification based selection is appropriate where there is no premise type within the data. And there are plenty of office-based companies which are far from ideal anyway; such as taxi companies or couriers. But where the premise type does come into play is as a sense-checking tool. i.e., that the business data specification caters for the removal of prospects which operate from an undesirable premise type.

Another premise type which yields a high volume of anomalies are the companies trading from home. Many services are simply not suited to this premise type. A company may be flagged up as “warehousing services” in the business classification and also be identified as having ten employees. But in reality this could be an individual who previously stated that they have ten employees, where those employees are either contracted or work from a different site. And all the company’s warehousing services are in fact contracted out, with this particular business operating on a commission scheme.

So whether applied as an inclusion or exclusion parameter, the premise type is of particular relevance when considering your marketing data and how best to specify it.

 

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Business Data Samples

There are three reasons to get business data samples when sourcing a prospect list;

(1) Data Qualification

(2) Quality Testing

(3) Review the b2b data Fields

 

DATA QUALIFICIATION

The first, Data Qualification, is your opportunity to manually check each sample record to ensure it meets with your business data brief. Some examples include; if you need every record to contain a director-level contact name then check the job title of each contact name contained within the samples. If there are any absent or managerial contact names then the samples have not married up to the brief. Check the geography of each record (town, county & postcodes) to make certain they are all within your desired catchment area. Check the employee size and/or turnover information to be sure every line marries up to the target market company size. And perhaps the most important data field to review is the industry classification (sometimes referred to as SIC code). Quite often our customers say that “any business” is an appropriate target, but in reality they did not consider that some business types are undesirable; government, schools, churches, care homes etc. So by reviewing the industry classification column you should be looking for any b2b data which (upon manually qualifying the samples) aren’t desirable after all.

So what the samples enable you to do is sense-check the business data you would be buying. And it is imperative that you do check each record.

 

QUALITY TESTING

Business data samples are supplied so that you may test a few records. It doesn’t take long to call through 10 to 20 records and ask one or two quick questions. First and foremost, is the phone active or dead? And when the phone is answered, do they give the company name as listed on the sample database you have been supplied? You could even check that the contact name given within the data list still works for the company and is resident at that premise. Auditing the company premise type is a good sense-check also (although part and parcel of the data qualification process above), but if the contact name supplied works at a different site or building, then the premise type is the first field I would check. Is it the head office or a retail outlet for example?

The quality testing process is there to check the accuracy of the data list; not to audit the data fields or how the file looks in terms of the specification. This step is purely to ensure the business data is current and reflective of what you might expect when ordering a larger file.

 

Review The b2b data Fields

The b2b data fields are effectively the columns within the spread-sheet. Many list brokers charge extra for additional fields. So although they may quote a very cheap price for company name, address & telephone number, the prospect list may be absent of contact names or the other profile variables. Profile variables include the business classifications, staff headcount, premise type etc. So this stage of the checking is really all about making sure that the content of each row is as you would like it. And if any fields are absent then ask; is the extra data available, and does it come at an extra cost?

 

Responsiva’s b2b data Samples

Responsiva supplies data samples with every new-customer quote, for the very purpose of these three processes. We want you to check the data quality, that the data meets the brief and that all the desired fields are within the file. With the exception of email addresses, all available b2b data fields are supplied as standard and at a simple rate per 1,000 records. It may not be the cheapest file around, but you get all the fields without having to pay those niggling costs for all the little extras (like when booking a flight!), which end up making the file more expensive anyway. And we definitely want you to check the quality of the data by making a few calls. A huge amount of money would be wasted on your telemarketers’ time if the quality is not up to scratch.

(the comment that Responsiva only supplies samples to new customers is purely because the repeat customers already know the data quality, fields supplied and qualification of the brief is at a high standard. That said, repeat customers can always request samples too).

 

So the data samples are actually a vital part of ordering business data; they are your opportunity to be satisfied that the prospect list is fit for purpose. If you would like some free business data samples then please contact Responsiva on 0800 118 5000, or send an email to info@responsiva.biz

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Using the business data Premise Codes

The premises type within the business data universe has genuine value to some business types. Most especially those targeting a specific kind of building rather than by industry classification. Three good examples follow;

 

1. Industrial Waste Disposal / Collection

By selecting a prospect list by specific industry classifications will yield anomalies. For example, the manufacturing sector appears at a first glance to be a great sector to market to. However, any marketing list which selects the b2b data by the manufacturing sector will contain an estimated 30% undesirable prospects. Not all manufacturing company premises are factories; many are offices, head offices and sites of administration, marketing & finance. And these could well be located literally hundreds of miles from the manufacturing plant. So by contacting the satellite offices to provide an industrial waste collection & disposal service would quite probably be a wasted marketing piece. The data list should be selected by factory premises; ideally with a minimum employee size to give a fair indication of the volume of industrial waste.

 

2. Fork Lift Trucks & Training

Virtually any business sector can have a storage facility requiring warehousing, though admittedly some are more prone than others. When identifying a business list for marketing, selecting the companies trading from an actual warehouse premises would be much stronger than using the regular SIC coding system. As with the first example, employee size will give an indication of usage (i.e., number of fork lift trucks required for sales or service, or number of trainees). The premise type is vital in so much that a head office based in a commercial tower block will have no fork lift truck related requirement. It could be argues that the head offices may make the decisions, though past experience suggests that they are more likely to allocate a budget for the warehouse manager to make the actual decision on which trucks and related training services are required.

There are two anomalies with warehouse premises however. Many large supermarkets, department stores and other retail premises have a warehouse facility at the rear. But by the very nature of their business they are classified as a retail outlet. And you would not wish to select retail outlets in general when identifying a prospect list for fork lift trucks, or you may scoop up all kinds of dross such as fish ‘n’ chip shops etc. For this reason, many of the warehouses are classified as a different premise type. But also, some businesses classified as a warehouse are chain outlets of a larger home improvements store, or commercial courier company. These can be excluded by the branch count however.

 

3. Office Services

Office services can range from photocopiers, partitioning, stationery and all manner of products which target the office premise. It could be argued that these services are also required in factories, warehouses and other premise types too. So the best example to consider would be p.c. related services (sales, services, networking etc). Specifically, where the employee count should have a high correlation to the number of people actually sat at a desk and using a computer. The office premise is ideal for this, but there are some anomalies. Taxi companies for one; 100 employees could quite literally mean one person sat at the reception desk and 99 drivers out on the road.

 

There are pitfalls in making any business data selection for your marketing. But at Responsiva you have the reassurance that with around 25 years experience these will be pro-actively explored thoroughly before the data is actually ordered. The business lists you order will be fit for purpose, accurate and well-defined.

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