![]() ![]() Your campaign is either effective, in which case repeating it should be a good thing, or it doesn’t meet the bar you’ve set, in which case doing more of it will likely lose money. Assumptions have no place here, folks, barring some situations (see non-trackable leads below). It has only one purpose: to evaluate the effectiveness of campaigns in order to decide which ones to keep and which ones to drop in the future. Let’s get back to the reason why attribution matters and why we do it in the first place. While this might create good feelings and justify a marketing budget short-term, it makes no sense and amounts to third-party validation of something that has little to do with reality. Here is an example: I sent an email to a person multiple steps removed from the current lead a long time ago should this be credited as an impactful interaction? A typical answer from marketing attribution tools would be yes or a weighted yes. It is a sound concept (yes, your outreach effort should be account-centric). You must have heard the term of account-based marketing (ABM). As a result, vendors bend over backwards to placate marketing (their target buyers) and sell them tools to claim credit for everything that comes in the door.Ī worrying trend over the last 5-6 years is the emergence of vendors that create weeks and months of work for the marketing team, encouraging them to configure (invent) a complex “model” under which they will claim credit for pipeline. Marketing tends to fret that they don’t get credit for their hard work (we agree with this, some of it is obscured from sight - more on this below). How does finance (and the rest of your org) evaluate whether leads have been generated economically? ![]() If sales is asking that you give them visibility to all of the one hundred leads, you can do this – but systematically indicate which ten are highest in quality. Giving sales the ten highest quality leads is much better than giving sales one hundred leads. Upgrade to machine learning-based scoring as soon as data volume and quality permit. The answer: this is a job for a machine, not a human. We also think that most of our colleagues wouldn’t know how to build such engines. ![]() They should take into account the characteristics of leads that do and do not convert to paying customers. Such models should take into account behavior, demographics, firmographics. We think most people would agree that better, objective models are needed to assign a better score. This generally results in a predictable rejection by sales. the score increases if someone has looked at an email and lowers if the lead has unsubscribed), the use of wholly subjective weights set by a human reflects this: what a marketer thinks should be not what really is. While this approach is directionally correct (i.e. This is not an objective measure and is highly likely to create idiosyncratic measurement (e.g., someone opening an email multiple times does not suggest that he is X times more likely to become an opportunity than a person who only did it once). A lead score value is thereby increased or decreased by an amount set by the marketer to the extent which s/he believes in something. The parameters of such scoring are typically set by marketing in response to certain interactions with a lead, such as sending an email to a lead, a lead clicking on an email, etc. The obvious expectation is that a higher score should correlate with a higher quality lead. Marketing has many tools at their disposal that help them with evaluating lead quality. But in fact, it doesn’t have to remain this way. Let’s just say there is a clear interface issue that typically remains unaddressed with an ingrained expectation that “this is how things have always been”. We won’t kick a dead horse in this post and belabor differing perceptions regarding the quality of leads generated by marketing. ![]() How do we measure the quality of B2B leads? Let’s examine each of these two objectives carefully and try to understand the best way to achieve both. This leads to an outsized focus on lead volume, to the detriment of quality and efficiency. In practice unfortunately, these objectives often get forgotten as marketing teams sustain pressure from the organization. There are two requirements to performant marketing: 1) to generate high quality leads, and 2) to do so as efficiently as possible in terms of resources consumed. We start this blog by stating the obvious. ![]()
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