How To Purchase B2B Data

Buying in B2B

For what should be a relatively straightforward part of the marketing process, buying in B2B data can be an absolute minefield. So to help you decide which of the many available sources will best suit your needs, D&B has highlighted the five fundamental areas you need to focus on to ensure the data you purchase makes a measurable difference to the ROI of your campaigns.

With finances under ever-increasing pressure, it’s important to squeeze every last drop out of your resources. So how can you improve your data purchasing, and transform it – from what can sometimes seem like a lottery – into a strategic pillar of your campaign ROI?

There are five key areas you need to focus on when considering potential sources for data purchase. By focusing on these areas, you should get a much better grasp of the strengths and weaknesses of a particular dataset and the kind of results you can expect to achieve from it – rather than waiting for the results of your campaign analysis to discover whether it did or didn’t meet your objectives.

1. Data quality

It probably won’t come as a surprise that data quality rather than quantity should be number one on your checklist, but it can still be easy to forget this – especially if someone’s just phoned you with an ‘unrepeatable offer’ that sounds too good to resist. Data quality is far more important than the quantity of data on offer, as it enables more accurate targeting than blanket marketing, and means that even small, high-quality databases are well worth considering – especially if they enable you to access decision makers that you wouldn’t otherwise be able to reach.

So how do you judge the quality of a particular dataset? Data quality can be broken down into key attributes including its age, accuracy, cleanliness, and completeness:

• The age of data can have many different aspects to it. So, for example, when a piece of data is updated, it’s important to know how soon afterward it will be made available for you to purchase, and whether this is in real time or periodic.

• Another way of looking at this is the average age of data in a file. As an approximate benchmark, an average age of six months or less is the minimum you should expect from your data.

• Even if you know when data was last updated, this too is open to interpretation.

– Each business in a dataset will typically have a record assigned to it, made up of elements including its address, postcode, telephone number etc. But are updates applied to individual records, the elements that go to make these up, or both?

– If a data provider defines an ‘update’ as calling a business’s telephone number to check this hasn’t changed, when was the call made and what other questions did they ask? If the business has moved while keeping the same telephone number and this isn’t covered during the call, its address details will be out of date, so it’s important to understand how frequently all the information about a company is updated.

• The methods used for updating data are therefore absolutely essential to data quality. If a provider relies solely on data from Companies House, for example, is that accurate enough for your purposes?

To summarise, in terms of data quality you’ll want to know:

• When a dataset was last updated.

• How frequently it is updated.

• The average age of the elements and records it contains.

• The collection methods and ‘sanity checks’ used (i.e. how robust is the data?).

• How clean and complete it is – as the last thing you want is to end up paying for duplicate or inaccurate records.

You may also want to consider the timeliness and ease of access to the data, for example by taking advantage of data that’s updated in real time and/or delivered to you automatically via data as a service (DaaS).

2. Data breadth and coverage

Because different suppliers have different ways of collecting and aggregating their data, coverage is a key aspect of every dataset – as you don’t want to choose one that’s missing a significant part of your potential market, or that doesn’t let you contact decision makers in the way that suits you best. You can look at coverage in different ways based on the businesses and/or individuals you’re intending to target:

• Typically this will mean considering the number of businesses and/or individuals in the UK that are engaged in a particular industry or activity, and how many of these a provider can enable you to access.

• You may also want to differentiate between businesses that are actively trading and those that are either dormant or have otherwise ceased to trade.

• One way to assess this is whether a provider has details of all organizations that are registered for VAT and/or PAYE. In March 2011, just over two million organizations, representing 99 % of UK GDP, met these criteria, and all of these are covered by D&B’s UK Trading File.

• Another key consideration is ensuring that the people in a particular dataset are happy to be contacted by you – so you’ll want to know which suppression files have already been applied to the data.

• For example, if you’re being supplied with data for telemarketing that includes people who are already registered with the telephone preference service (TPS), you could end up paying for records you’re unable to use.

3. Flexible targeting

Flexible targeting is all about being able to segment your campaigns based on the characteristics of the businesses and/or individuals you want to get in touch with, and the channels through which you want to target them.

• If you’re targeting IT directors, for example, you might be quite happy with a dataset that just lists their names and postal addresses.

• But if you wanted to target the IT directors of organizations above a given size or in a particular market segment, you’d need a dataset including broader company insights to enable you to do that.

• And what if you’d rather call or send them a personal email? Or you’re planning an integrated marketing and sales campaign with telephone follow-up? You’ll want data giving you all the separate pieces of information your sales and marketing teams need to do that as well.

• Depending on how focused you want a campaign to be, you’ll need data that gives you access to more and more of these kinds of insights. It’s all very well, for example, being able to target every single estate agent throughout the whole of the UK, but if you only want to get in touch with those in the London area with five or more employees, and a record of consistently outperforming the rest of the market, you’ll want to make sure that you only have to pay for these rather than for a much larger dataset, the majority of which will be of no use in meeting your objectives.

• For highly focused campaigns, the ability to use multiple criteria in identifying your targets is crucial to success, so you’ll almost certainly find the availability of specialist fields with which to target your universe – such as corporate family trees, the links between businesses that are part of a larger group, fleet information, business buying behaviours and budgets – more than justifies the investment.

• If this also includes the ability to support personalized, one-to-one campaigns specifically targeting the individual(s) responsible for making or influencing buying decisions related to your products or services, you’re almost certainly onto a winner.

4. Account management

Effective account management is about far more than giving you someone to speak to. The reason data is such an issue is that there are so many elements to it, and these are only going to increase as the focus of marketing turns more and more towards personalized and one-to-one campaigns.

Because of this, a data provider’s customer service capabilities are going to become increasingly important to your purchasing decision. There’s very little point, for example, in identifying what sounds an attractive dataset which then takes weeks for you to access – or a supplier that provides low-cost data, but where their data representatives have little or no understanding of your business or requirements.

Among the criteria you can use to judge a provider’s quality of service include:

• Their speed of service (such as turnaround times for requests).

• The knowledge of their data representatives and their willingness to guide you through the data identification and purchase process.

• Whether you receive a personal account manager as your single point of contact.

• Whether they can provide you with results of an independent audit or survey of their data and service quality – and if not, why not?

• You should also ask how quickly you can expect queries and issues to be dealt with, should they arise after your purchase.

5. Value (as distinct from price alone)

From the above, it should be clear that there are many different aspects you can (or should) take into account when considering a data purchase. What’s ultimately important, however, is that you derive maximum value from your data – which may well mean a very different calculation from one based on cost alone.

Essentially, the higher the quality of the data you’re able to purchase, the broader its coverage, and the better able you are to focus on and target the people who are most likely to buy from you, the greater the ROI of your campaigns will be. Combine this with excellent customer service and you’ll have identified a data supplier who can make a significant contribution not just to the success of your campaigns, but to your business moving forward.


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