Lead nurturing campaigns, generally delivered via automated series of emails, have long been an important part of online marketing in the B2B space. And for good reason–they are the best way to “nurture” a lead who isn’t ready to convert/buy by delivering timely messaging, helpful content, and repeated calls to engage with your business.

However, lead nurturing campaigns are often treated as “set it and forget it” initiatives, where less-than-ideal results are accepted as status quo for months or even years.

This is a shame, because like any marketing initiative, they can be improved using approaches that are being employed in website and landing page optimization.

This post will cover the basic approach I’ve developed when trying to optimize lead nurturing campaigns for my clients over the years. As such, it will be useful if you haven’t tried optimizing campaigns yet, and less useful if you’re looking for advanced techniques.

The Data You’ll Need

Just like conversion rate optimization, you must start with whatever data you have available. Besides qualitative marketing data (target segments, roles, personas, lead data, etc.), here is a basic list of the quantitative data you can use to benchmark the performance of a lead nurturing campaign:

1. Open Rate, from email service provider
2. Clicks/Clickthrough Rate (CTR%), from email service provider
3. Unsubscribes/Unsubscribe Rate, from email service provider
4. Landing Page Visits, from web analytics
5. Landing Page Bounce Rate, from web analytics
6. Conversions/Conversion Rate, from web analytics
7. Estimated/Actual Conversion Value, from web analytics or other backend system

This is not an exhaustive list, and generally the more data the better. But, this is a good basic starting point. Generally speaking, here is the direction each KPI should move in to indicate a successful optimization of the campaign:

1. Open Rate = ↑
2. Clicks/Clickthrough Rate = ↑
3. Unsubscribes/Unsubscribe Rate = ↓, or unchanged
4. Landing Page Visits = ↑
5. Landing Page Bounce Rate = ↓, or unchanged
6. Conversions/Conversion Rate = ↑
7. Estimated/Actual Conversion Value = ↑

While some marketing automation platforms may allow you to A/B test between nurturing campaigns (Control and Optimized), I’d wager most marketers don’t have this capability. This is why the list of metrics above is important; it will form your benchmark if you need to run a “serial” or “before/after” test to vet your optimized campaign. Now that we’ve got our KPIs figured out, let’s look at what you can optimize to move the KPIs in the right direction.

The Levers You Can Pull

Just like landing page optimization, there are certain basic levers you can try pulling to see what kind of lift you can get in your KPIs. For landing pages, these might be things like call to action buttons, images, headlines, and testimonials. For lead nurture campaigns, which are essentially just linked/timed emails, the basic list is a bit different:

1. Timing/Cadence – when the emails are sent after the trigger event; how they are spaced apart
2. Subject Line(s) – how the subject lines are linked to the overall campaign and optimized for opens
3. Copy Approach – long, short, factual, emotional, focused on credibility, focused on loss aversion, etc.
4. Nurture Approach – the most difficult element; how you move the lead from Point A in their buying process to Point B
5. Resources Offered – what elements are offered in which timed email; what’s in it for the lead?
6. Call to action – what you ask of the lead as they open each email in the series
7. Landing Page – standard landing page optimization tactics apply; only now you know with precision where the visitor is coming from!

Again, not an exhaustive list, but enough to get you moving towards an optimized campaign.

As with conversion rate optimization, you can choose to test each of the above 7 elements as isolated variables to understand their discrete impact on campaign KPIs, or you can choose to challenge the status quo with a “radical redesign” approach where you change some or all of the 7 elements at the same time.

Also similar to conversion rate optimization, I tend to begin with the radical redesign approach, then move to the more subtle isolation approach on subsequent tests. If you don’t have the ability to split test, you’ll have to decide what level of statistical significance you want to see on the lift you get. This is essentially a spectrum from 0% (I don’t care about statistical significance) to 95+% (I care about statistical significance, and accept the fact that I may need a huge sample size to reach it).

In any case, the complexities of statistical significance calculations on a before/after test of a multi-email campaign will need to be saved for another post.

In the meantime, I’d love to hear from readers what you think of my 2 lists of “basics.” Anything missing? Any optimization stories on lead nurture campaigns? Do believe this is a worthwhile pursuit?