We all want to see the strongest start to Q1, so now is time to make sure your B2B prospect database is optimised. But with the advent of GDPR and concerns about data quality – putting your data through an audit and refresh will ensure maximum accuracy, insight on key decision-makers and, of course, volume. The perfect trio for maximising response.
So what does a data audit involve and why do it?
Appending your current campaign data set
A data append involves taking your current campaign data set, and adding up-to-date contact information to these records. By doing this, you will make sure you have the most accurate and high-performing database, boosting response rates. So, if someone has left a business or changed roles, this process will provide you with the most up-to-date contacts you should be speaking with. With data decaying on average 30% over the course of a year, refreshing this now will have a huge impact on your Q1 success.
Top tip: Request a data append on your entire data criteria, rather than just on your current contact list. This will also inject any newly incorporated businesses that have been captured by your data partner – growing your marketable database even further.
Expanding your data criteria
If you’re looking to expand into new sectors and markets next year, a revised data count will visualise your entire data universe, mapping out exactly how many prospects you could be reaching.
This process simply involves running data counts on your key criteria, including industries, job function, size and location. Once presented with the data counts, you can make a decision on the best sectors for your campaign.
Top tip: It’s about starting broad and refining down to ensure a highly-targeted approach which will avoid you managing outdated or irrelevant records. If you’re unsure exactly which other industries to be targeting (is finance really a sector that could work for you?!) use this process as an opportunity to test the waters and select a sample from each industry. You can then run a segmented campaign to this data and review the results before committing to the full database.
Reviewing the decision-making unit
Are you just targeting one contact per business? If so, why not expand your data criteria further to include multi-contact data for a range of job functions. Again, you can test samples of different decision-makers to see which gets the best response. Once you have your decision-maker split, you can segment your messaging and create a much more personalised campaign for every prospect involved in the decision-making unit.
Top tip: Remember, if you are targeting multi-contact, adjust the messaging based on the unique pain points of each decision-maker – a marketing director will have different priorities and objectives than an MD – you need to leverage this in your communications to get the best results.
Analyse and segment
Based on your campaign performance this year, are you targeting the most profitable segments for your business with the right messaging? If you’re unsure, a segmentation analysis will help visualise this for you. By reviewing your messaging hierarchy, personas and historic campaign reporting, you will be able to identify where your strongest and weakest performing areas are. This knowledge allows you to optimise your strategy to ensure you focus on the best opportunities.
Top tip: Run a spend analysis at the same time. This will review where your revenue has been coming from historically. By knowing this, you’ll be even better placed to allocate marketing budget next year, knowing you’ll be putting it into the right channels.
Are you sure you’re really targeting your sweet spot? Why not take your current list of top clients, and run a look-a-like exercise to find more like them?
Look-a-like or propensity modelling looks at desirable traits or behaviours in your existing database to find out what types of records are top contributors to your campaign engagement or bottom line, and helps you find more businesses like them.
Once you have this, a data house can match this criteria against their database and present you with a list of ‘look-a-like’ businesses. This is the best way to go if you want more of the types of clients you currently have.
Top tip: You can also run a look-a-like on ‘dream’ prospects to ensure you are prospecting all the businesses you’d love to work with.
Choosing a supplier
When choosing a data supplier, it’s important to consider the below points in order to get the best possible outcomes, drive responses and keep your business compliant.
GDPR: With the new GDPR legislation now in place, it’s important to only use data partners whose licenses fit with your business’ GDPR stance. We recommend following the DMA and ICO guidelines for further information and asking your data partners to do the same.
Data usage: Data lists are typically leased or licensed rather than purchased outright. The benefit of this model is that your database will be refreshed at the point of relicense, so you continuously have up-to-date contacts. These contracts are typically for 12 months.
An important area to consider is the frequency you plan to broadcast to this data. Although a license will be for a fixed term – you will be limited on ‘number of uses’. This is to ensure that marketers are using the data responsibly and not ‘spamming’ contacts. Make sure you discuss the volume of sends within your marketing strategy so you take a license that is best suited to your business. These licenses are typically 12, 24 or 36 uses within the 12 month contract.
Importing the data: When importing this data into your CRM system, remember to include the expiry date and some form of tag, so you can easily identify the records that came from the data house. This will make it easy for you to keep track of the number of uses used throughout the year – ensuring you are compliant with your license.
Gemma Roalf is marketing director at Really B2B, a B2B marketing agency and sister company of Econsultancy.