We recently completed a three-part series on creating a nurture that fills your pipeline in which we covered, among other things, the benefits of automating the entire nurture. To do this, the functionality of the marketing automation platform needs to be correctly harnessed in order that the right content is delivered at the right time of the buyer’s journey, that this content can be delivered across multiple channels to suit the target audience and, finally, that the lead can be automatically assigned a score which ultimately determines its likelihood of delivering a positive commercial outcome. Wow, to be able to automate all of this is really pretty cool!
You will notice that, at no point have I mentioned using your marketing automation platform to blast out more email. And while email certainly has its place, there is nevertheless SO much more to your platform functionality and yet, for a variety of reasons, much of this functionality is often overlooked.
In my years of consulting with clients on getting the most out of their marketing automation, there are definitely 3 clear winners in the ‘most underused modules’ competition:
- Nurturing: so many organisations have nurturing functionality but don’t use it to its full potential
- Lead lifecycle: definitely top of the list, in my view
- Lead scoring: this functionality IS used, but unfortunately, often incorrectly
Let’s look at each of those in detail:
A nurture program is intended to take a lead on a journey and serve them useful and meaningful content along the way that maps onto the stage they’re at. Doing this correctly develops relationships with buyers at every stage of the sales funnel and through every step of the buyer’s journey. So often, though, people mistake nurture activity with just a drip campaign in which everyone receives every email in the program, and this leads to a double negative: a) nurture is not being done properly (i.e. content is not mapped to the recipient’s buying stage) and the results will be disappointing b) you are not using the marketing automation functionality that you’re paying for.
So, in the first instance, we strongly encourage organizations to take a good look at the journey they’d ideally like to take the leads on, and then decide how and what content should map onto this journey. Secondly, organizations should look at how they use the functionality within the tool they are paying for to make sure there’s a bespoke path for leads, even if delivering at scale.
Marketo Engagement Programs enable sophisticated nurturing programs to be created, often with multiple streams, in easy steps, and also give status updates and insights on lead engagement along the way. Using an automated system like this enables the leads to flow through at their own pace, so, for example, if you have a lead that is heavily engaged, you can set up transition rules to enable that lead to be served next stage content at a faster pace and, equally, if they’re not engaging at all, they may remain at the same stage for longer or move to a different stream. Similarly, if a lead is showing particular interest in a certain area, then this is useful insight on the lead and you can send them to a specific nurture about that topic.
To further illustrate my point, let’s say an organization has 4 different product offers, but they don’t know exactly which product a lead wants to hear about. You can set your marketing automation platform up to send a generic email ‘trap’ which would contain content for Product A, B, C, D. When we start seeing engagement, eg, a lead clicks on a Product A type article, then we have learned they have an interest in this product or area, and we can then start putting them in a specific Product A nurture track.
So Engagement Programs in Marketo is a good way to personalise the journey and allow leads to flow through at their own place, dictated by behaviour.
And other marketing automation platforms offer similar tools: Pardot Engagement Studios plans the nurture journey out in a flow chart format, for example: Lead comes in => send email 1. Does the lead open email 1? => yes => send them to email 4. So while the functionality is slightly different to Marketo in that it allows you to plan out the journey more visually, it effectively allows you to achieve the same result. Similarly, Eloqua Campaign Canvas also automates the nurture journey and allows leads to flow through at their own pace.
2) Lead Lifecycle
Within many marketing automation platforms you can build out a lifecycle – or revenue lifecycle – model, which offers a bird’s eye view of the different stages of a lead’s buying cycle from anonymous, to engaged, through to MQL, sales accepted and finally won (hopefully!). Such models show you where the leads are in the buying journeyas well as identify any sticking points. So, if you have a bunch of leads who seem to be engaged, but just don’t seem to be getting through to MQL, why is that? Is it because your scoring’s off? Is it because there are not enough opportunities for leads to engage to get to the next stage? Essentially, the lifecycle provides overall visibility and is a way for you to identify exactly where your leads are in the funnel, determine where there might be issues and then decide how you might troubleshoot to overcome those issues.
In addition to identification and resolution of issues – and consequently increasing the number of leads sent from marketing to sales – the lifecycle model also works in the reverse direction. When a lead gets passed back from sales to marketing for whatever reason – maybe the lead is not yet ready to buy, or perhaps they need more nurturing – then the feedback loop is there to help you determine the best next action. If a lead has been disqualified because, for example, they’re still in contract for the next 12 months, the feedback loop enables the marketing team to consider how best to communicate with the lead from that point because, after all, they’re not dead, and they’re potentially a good lead, so they need to be placed in a nurture based on the timing of their contract renewal. Similarly, a lead might be passed back due to budget issues, for example. Having this feedback means marketing can then place the lead into a nurture that is specific to pricing discounts, or end of Q4 offers.
So lifecycle models don’t just look at leads through a marketing lens, they also enable you to receive automatic feedback from sales and then automate how you then communicate with those leads moving forwards. Clearly the functionality needs to be optimised to do this, but, once it is, leads can flow into different nurtures and you can add in the reasons for being disqualified.
Similarly, you can automate fast tracks as well, so, for example, if a lead is initially anonymous, but they then fill out a ‘contact us’ form, they will automatically be promoted to being a ‘high value’ lead, and get fast tracked to MQL. Within Marketo, for example, you can – at a glance – report on how many leads are at this stage, or any stage, and the average time they tend to stay at a particular stage. This is extremely valuable information for marketing teams, but is so rarely used.
Fig 1: A simple success path lifecycle model, including the split between marketing and sales owned leads
Fig 2: A more complex lifecycle model showing possible detours
Marketing automation platforms offer so much in the way of powerful analytics and data that goes largely untapped. If you are not using this functionality already, or you have set it up but left it dormant, it’s really worth finding out how to set this lifecycle tool up or get advice on optimizing it for maximum reporting value.
3) Lead Scoring
I don’t believe lead scoring functionality is necessarily underused within marketing automation platforms, but perhaps misused, or not used to its full potential. At least in my experience of consulting clients. There are three common errors that we see on a regular basis:
(i) Taking the lead score at face value
Organizations become fixated on an overall lead score number, rather than looking at the context, ie, the blend of both lead behaviour as well as demographic attributes. Let’s say, for example, that a lead becomes a MQL at a total score of 80. The mistake often made is that, at 80, without looking at the story behind that score, the lead is simply passed to sales. But what if, for example, a student scores highly for engagement, having clicked on, or downloaded, every piece of content available, but all in the name of research and they’re never going to buy? Conversely, what if the CIO of a target account scores full marks on demographic attributes but has never engaged with any of the organization’s content?
To solve this, lead scoring models should factor in minimum scores for both behaviour and demographic attributes. To use our example above, if a lead scores 80, you could perhaps set a minimum behaviour score of 20, as well as a minimum demographic score of 20, in order to be confident that the MQL you pass to sales has shown both some engagement, and that they are somewhat of a good fit from a profile perspective.
(ii) Inconsistent scoring with new integrations
It’s important to consider all of the ways a lead could come into your marketing automation platform, particularly with the proliferation of possible integrations these days. The lead may be coming from LinkedIn, or – as we’re seeing increasingly since the pandemic – it might be through a virtual events tool like ON24, or from data integration tools like Integrate. Either way, all too often, these new pathways don’t get added into the scoring model and are therefore not accounted for. Lead scoring is not something you can set up and then just leave alone, it’s a dynamic process and needs constant monitoring so that, every time a new integration is set up, such as a webinar, and a new lead comes in, they need to be scored accordingly. Scoring needs constant attention, to ensure that new leads coming from new sources are not skipping the scoring mechanism.
(iii) Score global, and not by campaign
When scoring programs are set up at a campaign – rather than a global – level, you run the risk of double scoring as well as confusion about how records may have reached a particular scoring threshold. The lesson here is to keep your scoring global. If you need to nuance scoring for particular campaigns, that’s fine, but do so at a global level to avoid confusion and duplication.
The global marketing automation market size was valued at $4.06 billion in 2019 and is expected to reach a whopping $8.42 billion by 2027. And there’s good reason for this: at a time when Marketing Operations teams are stretched, these automation platforms help organisations implement successful marketing campaigns to generate and nurture quality leads, at scale.
But they don’t come cheap.
So if you feel you may be using your Ferrari to do the weekly shop, please do get in touch to find out more about how you can get the most out of your marketing automation platform.
 Grand View Research