The Critical Role of Trading Rules and Independent Referee Validation for Lead Quality
Written by Darren Griffin on December 12, 2023
When purchasing leads from third party suppliers on behalf of our clients, we enforce a set of strict trading rules through our purchase orders which allow us to reject leads that don’t fit our clients’ needs.
At the very start of the briefing process, we work to come to a consensus on an agreed lead specification for each campaign that the client, the third party publishers and LeadScale are all agreed upon so that only those leads that fit, are the ones that are purchased.
However, without strict policing you will end up buying leads that just aren’t fit for purpose.
In this blog post I cover 3 of the main areas that you should be patrolling when purchasing leads, what’s involved with each of these and why you should potentially consider using an independent referee to enforce the trading rules on your behalf.
A duplicate lead is quite a common occurrence when using multiple partners on the same campaign, in fact across all campaigns that LeadScale Services run, we typically see a 12% rejection rate across all campaigns. But of course, not all campaigns are the same, some campaigns will only have one publisher supplying leads, while some of our bigger clients could have over 10 publishers on plan at any one time.
An off-specification lead is a record that doesn’t meet the pre-agreed campaign specifications.
You’re obviously checking every lead to make sure that every lead is the right company size or revenue, the job title or function, the job level, the correct industry, their location.
You’ve gathered evidence for each of these variables. Right? RIGHT?
This is the area that we see most potential clients struggling with and where they end up causing so much friction with their sales team. You end up sending leads to Enterprise teams that should have gone to the SMB team. Private Healthcare leads to the Public Services team. A lead that should have been a Finance Manager is actually an IT manager…
Some Lead Management Platforms help with weeding out duplicates, contact verification and orchestration but one big weakness is that it is usually simple enough to manipulate a record so that it is accepted by these off the shelf platforms. Rejected because it wasn’t the right job function? Just change the job function to an accepted value and resubmit…
Every lead should be checked by a human against third party databases to ensure that each record exists, the firmographic details are true and then finally, that that record should be accepted as it conforms to the campaign specification.
Rejecting a lead because it has a personal email address is simple enough, you can set up rules to reject the well know providers.
But from there are you checking whether that business email address is valid?
If you are then you’re probably discovering the pain of catch-all email servers.
A catch-all email server is when a server is set up accept all emails and not return a positive or negative signal as to when an email address is live or not.
So, what do you do from here?
Your team should be researching for known company email structures to check whether that lead fits those structures before passing them into your system.
Phone numbers, are you auto-testing the given phone number to see that it’s live?
Rejection Rates and the Numbers Behind Them
We ran an analysis on a fairly large data set to see how many leads we were rejecting.
A little under 25% of the leads submitted by third party publishers failed our trading rules.
Duplicate leads were the largest, this was quickly followed by incorrect company size, incorrect job function or title, incorrect job level, incorrect industry, contact no longer at company, invalid email, bad data. After that we’re into a multitude of reasons that added up to a total of 11% of the rejections
Three primary areas to police, but it’s not a very simple process and some off the shelf solutions that are available to help you can be gamed.
LeadScale can provide independent refereeing that automates a lot of the checks around bad data and contact-ability, but also human verification, correction and evidence collection (using third party databases such as LinkedIn, Zoominfo, Hoovers, etc.).
If we can apply our trading rules on your behalf, we can potentially save you 25% of your demand gen budget from servicing records that should never have been purchased or entered into your CRM/MAP.
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