Attempting B2B marketing optimizations without accurate analytics is like flying blind. But which B2B analytics platforms are best equipped for certain types of measurement? And especially when a marketer is focused on down-funnel results, which optimization practices can help to achieve those revenue goals and KPIs?
We’ll discuss nine methods that B2B analytics can be used to optimize marketing strategies. All of these optimizations rely on accurate, granular data that serves to educate marketers’ decision-making practices.
B2B ANALYTICS 01 -- Use lead scores to trigger marketing activities and workflows
Marketing automation platforms often provide some sort of lead scoring feature. This is an algorithmic value that can fall within a specified numeric continuum. The more a lead engages with a company’s marketing activities (at least those measured within the marketing automation platform) the higher their lead score.
Note: Do keep in mind that these scores are typically only based on user behavior, not necessarily on persona or firmographic fit. For instance, an unqualified lead could spend a lot of time interacting with your content and be associated with a high lead score, even though their firmographics or technographics don’t fit your persona profiles. While lead scores are a helpful tool, they’re not a foolproof.
When the lead score reaches an agreed-upon value, it will trigger other activities. The lead might be automatically included in a lower-funnel workflow sequence that includes heavier content offers or stronger messaging. Or, it could prompt a sales representative to reach out with a personal email or phone call.
However the company configures their lead scoring paradigms, it’s the automation of the process that provides the most benefit. Rather than evaluating readiness on a lead-by-lead basis, lead scores allow the automation system to think for you. This is a prime example of how B2B analytics can make a huge difference within a marketing org.
B2B ANALYTICS 02 -- Use landing page conversion rates to prioritize content offers
Landing page conversion rates are far more than just fancy numbers -- they have the ability to reveal strengths and weaknesses and to infer additional needs for optimization.
Let’s say you send 100 prospects each to two landing pages, and one page converts at 5% and the other converts at 10%. At the end of the day, the second page will have generated double the leads even though an equal number of prospects viewed both pages.
This is the power of increasing conversion rate -- you don’t necessarily have to attract more prospects in order to generate more leads. Hence, you can use landing page conversion rates to prioritize your content offers. If one landing page is yielding significantly lower leads than another, you should consider removing the offer from your marketing workflows or outreach sequences.
Especially if you’re sending paid traffic to a low-converting landing page, it would behoove your team to either swap the offer, switch off the campaign, or make changes to the page that could/will increase conversion.
By making necessary changes based on actionable B2B analytics data, you’re allowing the numbers to make you money.
B2B ANALYTICS 03 -- Use A/B tests to enhance website navigation and page structure
In the previous section, we touched on making changes to a page or page element that could/would increase conversion. A/B tests are an excellent systematic method by which to accomplish this. There are numerous ways to create and run A/B tests, but at its most basic level, marketers create two versions of the same page and send traffic to both pages. After a set period of time, or when the page reaches a certain traffic number, the conversion rates are analyzed to see which page generated better results.
The key is to test isolated variables against each other. For instance, when A/B testing a given website page, don’t change the title, text, image, form, and button on version B. Why not? You won’t know which element(s) was/were responsible for the increase in conversion rate. (However, know that there are exceptions to this rule. When testing a high traffic page, there are ways to successfully accomplish multivariate tests.)
By changing isolated variables one at a time, you’re able to create a page that converts at the highest rate possible. It may take more time to test variables one at a time, but it’s well worth the patience and effort in the end. A systematic method for running these tests includes the formation of an A/B test hypothesis -- which Optimizely explains in fuller detail in their article.
Also, you can run A/B tests on more than just landing pages -- check out this comprehensive, detailed article from Optimizely on 71 things to A/B test.
[BONUS] Use full-funnel touchpoint data to optimize higher-funnel strategies based on lower-funnel results
Up to this point in our discussion, we’ve talked about how B2B analytics can impact top and middle funnel activities -- how they can generate more leads, or optimize the process of marketing & sales outreach. B2B analytics also have a deeper and more impactful function when applied to all stages of the marketing funnel.
As the trend toward revenue marketing continues (the idea that marketers are equally responsible for bottom-line impact as their sales team), full-funnel touchpoint tracking has become a key and coveted ability for B2B marketing teams. Full-funnel touchpoint tracking is the ability for a B2B analytics platform to assimilate the granular behavioral activities of individual users from the top to the bottom of the funnel.
If an analytics platform can follow the exact buying journey of a prospect (which ads, clicks, keywords, emails, content, landing pages, outbound calls, events, etc.) were responsible for moving a customer through the funnel, it has incredible optimization potential. B2B marketers can see precisely which activities generated leads, opps, and revenue (and which ones didn’t). This type of B2B analytics answers a marketer’s most pressing question -- what’s working?
The most powerful, comprehensive tool for this job is advanced B2B marketing attribution that provides net new data tracking at a touchpoint level. For the remainder of the discussion, the optimization tasks we examine will be based on this type of full funnel tracking capabilities.
B2B ANALYTICS 04 -- Use down-funnel conversion data to optimize paid search keyword bids
Most B2B marketers choose to optimize their paid search keyword bids based on click-through rate and lead conversion. However, granular touchpoint-level tracking solutions (like B2B marketing attribution) can track a website visitor from their first click through their entire funnel experience. So, a paid media manager can optimize their keyword bids on down-funnel conversion data.
When evaluating results based on these full-funnel B2B analytics, marketers often make unexpected discoveries. A common example is when a given keyword has a lower CTR or lead conversion rate, but it actually generates higher quality leads that prove more likely to convert to opportunities and revenue -- ultimately adding to the bottom line.
By looking at the down-funnel conversion data of top-of-funnel activities (like keyword bids) marketers can see whether they’re only paying for clicks, or whether they’re actually paying for customers. As Matt Heinz from Heinz marketing likes to say -- you can’t buy a beer with a lead.
B2B ANALYTICS 05 -- Use win rates to optimize campaigns targeted toward opportunities
Win rate is easily one of the most exciting metrics. While leads, MQLs, and opps still have a long journey ahead of them, win rates represent actual closed revenue. As such, the win rate metric can be used to optimize campaigns and activities targeted toward opportunities.
Ad campaigns, email workflows, direct mailers, outbound calls, and other activities can be directly compared against the win rates affected by those activities. This is a simple task when you’re equipped with the right B2B analytics tools, such as B2B marketing attribution. Each touchpoint caused by one of these down-funnel activities is represented in the overall customer journey, so revenue credit is attributed accordingly.
If you’re interested in looking into this topic, take a look at this article about How to Perform Actionable Win Rate Analysis. Jordan Con explains that, “Win rate is an essential bottom-of-the-funnel marketing metric. Measuring win rates gives B2B marketers a constant gauge of how well marketing efforts are converting prospects, especially at the bottom of the funnel.”
B2B ANALYTICS 06 -- Use revenue analytics to measure ROI of events, trade shows, and conferences
Revenue analytics track all touchpoint (both online and offline) directly to revenue and show how those activities contributed to the bottom line. In the case of events, these conferences, trade shows, and field marketing ops are huge investments, so it’s critical to show direct revenue impact. While events can generate huge numbers of leads, it’s questionable whether or not those leads are qualified, or have reliable potential to become customers.
As a result, revenue marketers can use B2B analytics to justify good event sponsorships and rule out options that haven’t proven to generate enough ROI. For example, our team at Bizible ran this analysis after we attended a large set of events in 2016. This year, we’ve considerably limited our sponsorships, and you can read more about why.
B2B ANALYTICS 07 -- Use lead-to-account mapping to coordinate outreach by company
While lead-to-account mapping is primarily useful for account-based marketers, even demand generators can see significant benefits from using B2B analytics to organize their leads according to an account. Especially when leads are handed over to the sales team, if the representative can see that four key personas at the company have engaged with marketing initiatives (ads, content, emails, etc) they can optimize their plan for sales outreach. However, if sales reps are separately contacting leads who sit next to each other, it’s often a waste of everyone’s time.
And, if your team is implementing an account-based marketing strategy, mapping leads to their accounts are a huge part of the process moving forward. For more information about lead-to-account mapping in Salesforce, download this step-by-step guide that outlines both the technical and strategic requirements necessary to make the switch.
B2B ANALYTICS 08 -- Use predictive engagement scoring to bolster ABM orchestration
Predictive account engagement scoring is an algorithmic metric generated by advanced B2B analytics platforms that support ABM orchestration. Predictive analytics take past engagement patterns and assign a score to that account. The score helps marketers and salespeople predict the best time for further outreach. In essence, (much like a lead score) the predictive account engagement score can serve to trigger marketing or sales activities.
B2B ANALYTICS 09 -- Use forecasting analytics to accurately predict future performance based on past data
Advanced, B2B marketing attribution solutions can also offer forecasting analytics that help to predict future performance based on past data. These analytics features can help marketers reliably reach their goals and accurately predict future spends and the associated return on investment. This is one of the most complex forms of forecasting because it relies heavily on accurate data that follows very specific modeling structures.
For more information about how to use these types of forecasting analytics, take a look at this post about How To Forecast Revenue, Hit Revenue Goals, And Look Smart In B2B Marketing.