Marketing automation platforms help marketing professionals identify revenue opportunities based on interactions and behaviors with a prospective company. Using the right metrics in demand generation will show how a marketing automation strategy drives revenue and connects with customers.
Find the right data on the dials to measure marketing performance
With companies adopting Web 1.0 technologies in the 1990’s and the Internet reaching the masses, marketers struggled to learn how to measure their impact to the business. Email marketing reached a fever pitch with the promise of promoting e-commerce Web sites to consumers and businesses in the New Economy. Marketing teams still measure bullet point items like click-thrus, impressions, open rates, number of site visitors, and more. Even senior-level marketing executives could not connect the path between these activity metrics and impact to revenue. Even today marketing managers and executives just look for higher activity numbers – more site visitors, more webinar attendees, more tradeshow leads and on. This type of analytical behavior places higher values on quantity over quality.
Now it’s more important to have higher quality leads that are ready for sales to engage versus a bucket of thousands of contact names with no identified or qualified interest. Marketing automation can help marketers identify the campaigns that produce the highest quality leads that generate the most revenue with the lowest cost. This informational is powerful and empowering.
Here are some general examples of data to analyze and build the complete picture of how a marketing automation strategy impacts revenue.
1. Inquiry conversions – Measure conversion performance from initial contact through nurturing, opportunity, win/loss.
2. Marketing Qualified Leads (MQL) – Leads that meet agreed on qualification criteria that move to sales for further qualification and prospecting
3. Sales Qualified Leads – Track the percentage of MQLs that develop into Sales Qualified Leads. Also track the percentage of leads that sales disqualifies.
4. Sales follow up – Track the percentage of MQLs that are contacted by sales
5. Fallout – Track the percentage of leads that drop out of each stage of the marketing funnel and sales cycle. Identify opportunities to minimize dropoff
6. Conversion to Revenue – What is the overall picture of revenue generation from demand generation. Revenue per month, quarter, year.
7. Revenue per Campaign – Analysis that combines qualitative and quantitative analysis. Too often the old school method of direct marketing permeates marketing that more is better. Revenue per campaign may show the most effective campaigns produce the fewest number of leads. But, those leads may produce the highest revenue.
8. Cost per Campaign – Again, the lowest cost campaign may produce the highest revenue or highest volume of qualified leads.
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Using Web 1.0 metrics will focus on incomplete data and miss the whole story a strategic marketing function needs to tell. The list above provides ideas on the metrics to analyze to determine impact to revenue and the overall support of strategic marketing objectives. Focus on combining the quantitative data with qualitative over a period of time.~
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