Intent VS Quality VS Scale

Hey! Thanks for taking the time to read my newsletter! If you’re not already following me on LinkedIn - go ahead, don't be shy - I often post about these issues outside of the newsletter. This is my 5th newsletter since I started this last month. So far the response has been overwhelmingly positive. 

If you haven’t yet, please check out my previous articles: 

• #1 was about about How LinkedIn Changed The B2B Marketing Game. I wrote about how I see the changing landscape of B2B marketing and the oversized role that LinkedIn has been playing here.
• #2 was Marketing and Sales - Align or Die. I explained how I see the biggest roadblock to B2B revenue success being the alignment of marketing and sales. I keep having conversations about this - week after week - about this being the biggest problem we're facing as B2B marketers.
• #3, I wrote about Revenue vs. Brand Awareness for SaaS Startups, and how the main goal of all advertising should be to create sales.
• #4 tries to answer the question Will LinkedIn Ads Work For You? A question I get a lot, and has different answers for different companies. I try to break down the various elements that might make or break your attempts at LinkedIn Ads success.

In this issue, I'm going to write about something that comes up often but is rarely understood: balancing buyer intent with lead quality and scale.

What is buyer intent?

Buyer intent is the level of readiness your lead has to become a customer.

SDRs often qualify leads using something called BANT (budget, authority, need and timeline)*, when they reach out to a lead to determine if this lead is a good fit to be passed on to sales for a demo.

*Personally I find this method to be out-dated for category-creating fast-growing startups. This lead doesn't have budget or a timeline for your technology that didn't exist five minutes ago. She may have authority and need, but that's not a given.

Beyond BANT, the source of the lead is a good way to determine the level of intent.

A lead that signed up for a product demo via organic or paid search - searching for your brand name or your main keywords (the ones that describe your solution's category specifically) tend to have higher intent that a lead that downloaded a whitepaper via a Facebook ad.

Balacing Your Resources

When you're allocating your resources - not just your budget but your time and the time of the people you work with - you need to trade off between intent, quality of leads and scale - and cost.

Imagine you have multiple sources of leads. Each source produces leads at varying rates of conversion from visitor traffic - but this is really just the tip of the ice-berg.

Looking at Quality

In order to understand the quality of the leads coming from different channels, you will need to begin to track quality of leads.

In B2B, usually this means the relevancy of the lead's role and the type of organization (industry, size) or if they use a certain technology, or a work on certain types of projects, or have a certain amount of salespeople.

I call quality leads MQLs, but some people use that to mean something else. Sometimes there is a scoring system, and a quality lead would be anything above 60, or above B - it doesn't matter what you call it. Track quality of leads. Once you do this, you'll be able to have a better picture of not only how many quality leads you're getting from each source - you'll see the quality level of the source.

For example here - and this is often the case - Facebook Ads have delivered a lot of leads, but those leads are of a lower quality than almost any other source. This is usually because there isn't a great way of targeting company size, industry and job title on Facebook - vs. LinkedIn which allows us to target by these criteria quite easily.

Search as well delivered a lower MQL rate. We can't control for B2B firmagraphics there as well - so SMBs as well as Enterprises might be searching for your keywords, even if you only sell to Enterprises.

What about intent?

The SQL rate is where you find the intent level.

For example here, for Google Ads, the MQL to SQL rate was nearly 78%! That means that of the 3/4 of relevant leads that you converted were willing to set up a demo/call with sales.

For LinkedIn, this was much lower, and for Facebook - non-existant.

And that brings us to our next measurement: cost.

Show me the money

This is where the picture starts to come to together.

Measuring the cost of MQLs and SQLs - not just leads - shows us how much we're paying for intent.

Looking only at the cost lower cost of leads from Facebook without seeing that these leads are of a lower quality, and have lower intent would suggest that you should put all your budget on Facebook ads. In this example, with just this data, it would be clear that you should actually stop running Facebook ads and put the budget elsewhere - to Google and LinkedIn perhaps - but where?

Let's break down the various campaigns, and see where you can balance this all with another overlooked factor: scale.

Will it scale?

To answer that question, one needs to dig deeper into the campaign data - to see what are the specific types of campaigns that are running, and what they're bringing. This doesn't get into the granular level of banners, targeting, etc. Just what type of campaign.

What do we see here?

Google:

1. Google has good CPSQL - but mostly for the brand campaigns (keywords with your company's brand name), and those aren't usually scalable. You're getting all there is to get there.
2. Competitors KWs get a decent CPSQL - and those might be scalable - but only to a certain degree.
3. Core KWs would be the best bet for scale here, but CPSQL is not as good.

LinkedIn:

1. LinkedIn looks different at this level. The content campaigns get a good CPL and just as high a MQL rate as the Demo Request campaigns, but the Demo Request campaigns get a much higher intent - with an MQL to SQL rate of 35%.
2. Overall, it would make the most sense to invest more in the Demo Request Campaigns - even if the leads and MQLs are much more expensive.
3. The LinkedIn audience is scalable - and we would be able to get similar results at x2 or x3 the scale.

Bottom Line?

It's always important to look beyond the top-line numbers at the level of quality and intent, and understand the nature of your lead sources to understand if it makes sense to scale.

To understand what the quality of your leads are, you must track MQLs and look at lead to MQL rates to understand the quality of your lead source.

To understand intent levels, look at SQLs - and MQL to SQL rates to measure the intent levels of your campaigns.

Thanks for reading! If you made it this far you truly are a B2B Marketing Champ!

Feel free to ask questions or just chime in in the comments - I'd love to hear from you.