Demand Generation Analytics: 10 B2B Metrics that Actually Matter

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What is measured can be improved.

There’s rarely a shortage of data for B2B marketers to compile. Demand marketers, especially, are drowning in data. But, data is only as valuable as the actionable insights you can extract from it.

How do you know which metrics matter and how to combine the right insights to improve your program?

How do you avoid “vanity metrics” that only serve as a distraction?

When it comes to demand generation, focusing on the metrics that matter can provide helpful insights to improve the effectiveness of your marketing campaigns and give a boost to your results.

But, what metrics actually matter?

Demand Generation Analytics: 10 Important Metrics

Metric #1: Closing Percentages

Closing percentage is a metric used by sales teams for decades. Still, this metric has immense value for B2B organizations where sales, marketing and customer success teams are all driving for the same goals.

Formula:

(Deals Closed Number/Sales Proposals Number) x 100 = Closing Percentage

What it Reveals:

  1. How effectively you’re qualifying and nurturing marketing-qualified leads.
  2. Weaknesses in bottom-of-funnel marketing efforts
  3. Need for smoother MQL-to-SQL conversions and handoffs
  4. Problems with sales proposal quality

Metric #2: Funnel Conversion Rates

The success of demand generation marketers isn’t measured solely by the total number of marketing-qualified leads (MQLs) generated, or on their conversions to sales-qualified leads (SQLs). Funnel conversion rates are often a deeper, more nuanced look into the quality of your full-funnel marketing efforts.

Formulas:

  • (MQLs/SQLs) x 100 = Top-to-Middle Funnel Conversion Rate
  • (SQLs/Customers) x 100 = Middle-to-Bottom Funnel Conversion Rate
  • (MQLs/Customers) x 100 = Top-to-Funnel Conversion Rate

What These Reveal:

  1. Weaknesses in your top, middle, or bottom-funnel marketing efforts
  2. A need for better demographic, firmographic, or behavioral qualification criteria
  3. Deficiencies in alignment between marketing, sales and customer success

For a deeper overview of full-funnel measurement, read into Demand Marketing Template: Getting Started with Funnel Measurement

Metric #3: Cost of Customer Acquisition

Cost of customer acquisition (CoCA) is one of the most critically important metrics to determine the sustainability of your entire demand generation program. The cost of customer acquisition must not be greater than customer lifetime value, or you’re in hot water.

CoCA is also incredibly valuable when drilled down to persona type, campaigns or other subsets of your demand generation plan, to provide a full-funnel view into the most cost-effective pathways to customer acquisition.

Formula:

(Sales and Marketing Spend/Customers Acquired) = Average Cost Per Customer Acquired

What it Reveals:

  1. Opportunities to achieve resource efficiency in marketing and/or sales
  2. Cost-effective persona subsets, campaigns or other demand marketing subsets
  3. Trends in the ROI of your marketing and sales over time

To learn more, we recommend the Integrate blog How to Measure Demand Generation: 13 Expert Tips.

Metric #4: Cost Per Lead

Marketers are generally familiar with the cost-per-lead metric (CPL). It’s been a major KPI for B2B marketing programs for a long time.

While the cost per lead isn’t the only type of demand generation analytic that matters in 2018, it’s still an important one. It can be especially valuable when you measure the cost per lead by lead source, or using this intelligence to get a look at the bigger, full-funnel picture.

Formula:

(Cost of Inbound and Outbound Marketing/MQLs) = Average Cost Per Lead

What it Reveals:

  1. The returns in MQLs of demand marketer’s lead generation efforts
  2. The success of a marketing campaign and/or lead generation source
  3. The value of a persona and related targeting criteria

Metric #5: Average Deal Size

The average value of each new customer closed within a specified period of time is your average deal size. For some companies that don’t rely on subscriptions and rarely have an opportunity to make repeated sales, the average deal size is usually the same as customer lifetime value.

Average deal size is a valuable metric for defining the success of demand marketing, but it can be especially valuable if you’ve refined your targeting parameters fill your sales pipeline with higher value opportunities. It can also be valuable for organizations who have recently released new pricing structures, messaging, products or other strategic changes.

Formula:

(Total Revenue Closed/Number of Closed Accounts) = Average Deal Size

What it Reveals:

  1. The average initial value of your new customer relationships, and if applicable, changes in value over time
  2. The impact of strategic or directional changes on your new customer revenue
  3. The value of personas or targeting parameters when average deal size is drilled down by persona or account type.

Metric #6: Lifetime Customer Value

Lifetime customer value (CLV or LTV) is the average value of your organization’s customer relationships for the duration of the customer lifecycle. For some B2B business models, such as subscription-based software or professional services, LTV is a crucial measure of how effectively the business is providing a great customer experience.

Formula:

(Total Customer Lifetime Spend/Total Customers) = Average Customer Lifetime Value

What it Reveals:

  1. The efficacy of customer-focused demand generation, account management and customer engagement
  2. Customer satisfaction, loyalty and retention
  3. Upsell and cross-sell success
  4. When drilled down by persona or customer segment, the quality of acquisition channels, retention strategies and targeting parameters.

Metric #7: Lead Velocity

What on earth is lead velocity?

While this approach to demand generation analytics may be a relatively recent addition to many B2B marketing metrics portfolios, it’s no vanity metric. Lead velocity is incredibly valuable, especially for marketing operations optimization.

By measuring the speed at which your demand generation program is scaling contributions to the pipeline, you can understand the success of your efforts to scale your B2B marketing upward. This metric can also provide insights into opportunities for improvements in targeting, middle and bottom-funnel marketing efforts, as well as the best channels for a multichannel demand generation strategy.

Formula:

(Total SQLs This Month/Total SQLs Last Month) x 100 = Lead Velocity Percentage

This formula for lead velocity is just one approach to measurement, which reveals the success of your efforts to scale up your pipeline. Other approaches take lead speed through the funnel, or both quantity of MQL-to-SQL conversions and funnel speed into account.

We previously discussed other approaches to measuring velocity and their unique value in the Integrate blog Lead Velocity: Why It Matters, What to Measure & How to Boost

What it Reveals:

  1. Success of efforts to scale up demand generation efforts
  2. The quality of sales-marketing alignment efforts and impact on revenue
  3. The efficacy of lead targeting and qualification criteria
  4. The value of newly added personas, demand generation channels, or campaign strategies

Metric #8: Marketing Impact or Marketing-Attributed Deals

At some organizations, not all customer acquisition activities represent marketing-attributed efforts. In these cases, understanding the pipeline and revenue value of newly closed customers that were generated or influenced by marketing can demonstrate the impact of your demand generation efforts on revenue.

When applicable, marketing-attributed deals should be measured periodically, including quarter-over-quarter, to understand how the value of your B2B marketing is trending over time.

Formula:

(Marketing-Influenced Customers Closed Number/Total Customers Closed Number) x 100 = Percentage Marketing-Attributed Deals

What it Reveals:

  1. The value of your demand generation efforts
  2. Trends in the impact of your demand generation

Metric #9: Cost per Lead by Lead Source

Wait, is the ROI and average CPL for your individual top-funnel lead sources distinct from average CPL?

Well, yes and no.

The general method of calculating these two metrics is effectively the same. However, this metric bears mention because it’s critically important for the success of demand marketers at running data-informed strategies, especially in programs where many different paid lead sources are used.

All too often, marketers lack the tools to effectively understand the value and cost of their top-funnel efforts. This is problematic. If you can’t see the big picture, you can’t understand the nitty-gritty details, like the lead sources that perform best by persona, target-account type or other important insights. With demand generation technology for visibility across the top of your funnel, marketers can make the most of their lead generation budget.

Formula:

(MQLs or SQLs Number by Source/Total Advertising Investment by Source) = Average Cost by Lead Source

What it Reveals:

  1. Average cost and ROI by top-funnel source
  2. Top-funnel source performance by persona type or other segment criteria

Metric #10: Stage Progression

Ever wish you could have a single dashboard that revealed your entire sales pipeline in a tidy, little bar chart?

Well, you can with “stage progression.”

This isn’t really a metric, but it’s definitely a valuable approach to measurement, so it bears inclusion on the list.

Essentially, a stage progression graph is a bar chart which shows the total number of leads and opportunities in each stage of your funnel. Depending on the length of your sales cycle and defined funnel stages, this may include:

  • Total Number of Marketing-Qualified leads
  • Total Number of Sales-Assigned leads (SALs)
  • Total Number of Sales-Qualified leads
  • Total Number of Opportunities
  • Total Number of Proposals
  • Total Number of Closed Customers

Optional, When Valuable

  • Total Number of customers Up-Sold, Cross-Sold, or Re-Signed
  • Total Number of Customer Referrals

Pro Tip: Some of the sharpest B2B marketers maintain a stage progression dashboard, and never enter a sales/marketing meeting or huddle with their boss unless they’re armed with this intelligence.

What it Reveals:

  1. Marketing and sales progress towards monthly, quarterly or annual goals
  2. The health of the sales pipeline and opportunities for funnel-stage improvement
  3. Opportunities for action, such as top-funnel lead generation efforts or middle-funnel accelerator campaigns
  4. When leads and customers are graphed next to historical data, improvements over time in marketing, sales and customer success efforts

One Thing You Need to Know About Demand Generation Analytics

Dated demand generation analytics don’t always offer the insights B2B marketers need to make the right decisions.

Data-informed success in demand generation requires measuring the right things, but it also requires marketers to act on the right insights at the right time, which is real-time. In 2018, marketers face rapid changes in persona behaviors, the best demand marketing channels and other variables that can impact the results of demand generation campaigns.

With real-time performance measurement and optimization tools, demand marketers can unify data from across lead sources, the MAP and CRM to understand and fine-tune full-funnel marketing performance without any lag in accessing intelligence.

B2B marketers know the changing game of marketing necessitates closed-loop measurement. However, there are definite obstacles that can prevent closing the loop, especially with outbound and non-digital marketing efforts. Learn how best-of-class demand generation planes approach measurement in the free Integrate resource: The Closed-Loop Era: Breaking through the Cloud to Full Visibility Marketing.

Republished with author's permission from original post.

Kate Athmer
Kate Athmer is the VP of Growth at Bombora. Primarily responsible for generating demand and fueling growth for Bombora, she’s constantly looking for optimizations, testing new strategies, and finding ways to help customers extract more value from their investments in Intent data - and beyond!

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