Welcome to the Responsiva Data Lists blog

Visit the Responsiva Data Services website

Posts Tagged business data

Specify Business Marketing Data

Thumbnail2

Specify the right business marketing data for your next initiative.

, , ,

No Comments

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

, ,

No Comments

Taxi Business Data Lists

Taxi companies will appear on most business data lists, yet they are probably the most unwanted of all industry classifications.

So why are they such an issue, and what can be done about it? There are four key reasons that taxi companies become an issue when specifying business data for marketing;

 

1. Vertical Market Selection: Transport Sector

Taxi companies sit within the Transport Sector. And although it would be normal to consider this sector to predominantly contain couriers, shipping and road haulage companies, taxis also reside in this sector. If considered carefully, to what other possible sector could they belong?

A similar example would be to select the “Education Sector”. Within this sector you would expect schools, colleges, universities, training companies and could even understand nurseries. But the industry classification which is perhaps the least expected is driving schools. There are many thousands of them, and they are not the kind of environment where you may wish to market books, pencils and other educational equipment.

 

2. Company Size Selection

Another typical business data brief would be to select all large companies (say, 50+ employees) within a given catchment area. And here is where the unwanted taxi firms pop up yet again. There may be just two or three people actually employed within the company, with each driver being self-employed or contracted. Either way., for the purpose of reflecting a company’s size, taxi firms will generally tot up the total number of people working for the company; and that includes all the drivers on the books. So it becomes commonplace that taxi operations are classified as having more than 50 employees from the perspective of the business data selection.

 

3. Office Premises

In marketing to office premises, businesses will usually have an office related product or service. Such as office cleaning, office equipment, stationery or even IT services. Each one of these services will usually target businesses by a minimum employee size (e.g. 10+) to ensure a reasonable sized sales opportunity. Cleaning an office with 10 staff will possibly mean 2 – 4 hours worth of cleaning per week. But a taxi firm is typically one person behind a desk, operating a phone and single p.c.. So the IT company would not be best chuffed with this opportunity either; 10+ employees in an office will typically mean there is a server linking all the p.c.s, where as a taxi operation is unlikely to have this. But how else could a taxi company be classified? They are not factories, medical centres or even retail outlets in the regular sense.

 

It becomes easy to appreciate why business data selections should apply a “special case scenario” to taxi firms; although some marketing campaigns would welcome them, in many cases they are a blatant and unwanted anomaly. And this is made worse by …

 

4. Population Count

There are some 17,000 taxi companies within the UK. Taking one postcode area as an example (Birmingham), a general business list selection from this region would include more than 300 taxi firms. That is a lot of unwanted data if these are not your target market. By contract, there are only circa 60 taxidermist companies UK-wide, so if these were unwanted (from a pool of over 3million records) then they would hardly dilute the power of your marketing initiative by including them. And that’s the point; there are so many taxi firms that their undesired inclusion would weaken any marketing database.

 

So What Can Be Done?

At Responsiva, one of the first questions you are asked is what product or service you supply. And the very reason for this question is so that consideration may be given to potentially undesirable industry classifications and other pitfalls. It is commonplace that a company would tell Responsiva that they have historically purchased a business list which includes them, ridiculing the b2b data supplier for not understanding their target market. It is true that business data suppliers sell on volume, so by including undesirable taxi firms within the marketing list usually means their sale value is higher. But it would be wrong to suggest any malpractice that they have attempted to pepper the file with useless prospects simply to up the sale value. It is far more probable that the client was serviced by an inexperienced account manager who simply didn’t understand the business universe well enough to know that taxi firms are one of the main anomalies when it comes to selecting business data.

, ,

No Comments

New Business Data Vertical Markets

Over recent months Responsiva have developed a new suite of business data groups, or vertical markets.

When seeking out a new prospect list, one of the most daunting tasks is sifting through the industry classifications to identify the good from the bad. With more than 2,000 classifications to choose from, this process can take several hours and requires the manual intervention to ensure accuracy. Responsiva has now amalgamated all of these classifications into a succinct list of 35 vertical markets. Just over two million of the b2b data records can be classified, with counts and percentages as follows;

Vertical   Market  Business Count % of Universe
Business   consultants & Training                      73,134 3.6%
Catering                        7,527 0.4%
Cleaning   Services                      26,454 1.3%
Computers,   Software & Hardware Consultancy                      70,483 3.5%
Construction   & Demolition                    182,503 9.0%
Education   Sector                      68,839 3.4%
Farming &   Agriculture                      60,356 3.0%
Finance &   Accounting                      58,958 2.9%
Food   Production                      12,309 0.6%
Hotels, Bars   & Restaurants                    173,701 8.6%
Insurance                        8,435 0.4%
Legal Services                      15,470 0.8%
Manufacturing   & Engineering                    141,888 7.0%
Marketing, PR   & Advertising                      12,468 0.6%
Medical Sector                      85,028 4.2%
Membership   organisations & political parties                      47,113 2.3%
Mining &   Raw Materials                        2,763 0.1%
Motor, Repairs   & Fuel                      83,222 4.1%
Personal   Services                      92,742 4.6%
Photography   & Media                      21,737 1.1%
Printing &   Publishing                      21,990 1.1%
Property                      83,295 4.1%
Public Sector                      10,488 0.5%
Recruitment                      16,529 0.8%
Recycling   & Waste Management                        8,244 0.4%
Rental Sector                      19,827 1.0%
Retail                    263,610 13.1%
Security   Services                        7,013 0.3%
Social &   Charity                      55,378 2.7%
Sports,   Leisure & Recreation                      76,868 3.8%
Surveyors,   Architects & Testing                      55,465 2.7%
Telecoms                        9,295 0.5%
Transport   & Storage                      78,586 3.9%
Utilities   (Gas, Water & Electricity)                        3,091 0.2%
Wholesale                      64,529 3.2%
Totals:                2,019,338 100%

 

Within each of these business data vertical markets resides every possible business classification. For example, within the group “Hotels, Bars & Restaurants” there is every business classification listing from pubs, wine bars, guest houses, hotels, all forms of restaurant (Indian, Chinese, Italian etc), take-aways, internet cafes, tea rooms to any other establishment you would associate with either overnight paid accommodation or having a meal or drink.

In applying these business groups to any data selection, the buyer is able to quickly identify the particular areas of interest or exclusion. Furthermore, if any further explanation is required of a particular group then this is easily expanded to illustrate the full listing of sectors therein.

To demonstrate the value of this new business grouping tool, for July 2013 only Responsiva are offering to apply it free of charge to your business database. Provided your database already includes industry classification or SIC codes (as all good business databases do) we will apply our new business grouping model to your file without charge.

 

What is the Value of this Tool?

Responsiva would normally charge £200 + vat to apply this business group model, so already there is a cost-saving by receiving this free information. But its true value and purpose is during the measurement of your campaign success. i.e., where are your positive results coming from? These business groups enable you to swiftly analyse your campaigns (or Responsiva will offer to do this for you) and enable you to identify future prospect data from within those high performing sectors.

If you have any questions regarding this new field, please give Responsiva a call on 0800 118 5000.

 

 

1 Comment

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.

 

, , , , , , , , , , ,

No Comments

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

, , , , , ,

No Comments