How to Set Realistic Objectives for Your Next Marketing Campaign
Discover how to use data analysis to set clear, realistic objectives for your next marketing campaign.
Discover how to use data analysis to set clear, realistic objectives for your next marketing campaign.
Most Marketing Managers recognise this situation: "We need 10% response rate from this campaign or it doesn’t work for us."
The request – from the Marketing Head, Sales Director, or other budget holder – is fair enough. But aiming for one number, in isolation, carries risks.
If 10% is where you need to go... you need to make sure you’re starting from a place that makes it achievable. A method called business data analysis can help.
To get where you’re going, start from the right place
Much business data analysis is about asking the right questions. "We need 10%" isn’t the right one. So it’s useful to rephrase. Try asking your budget holder: what has success looked like in the past?
If 10% is the target because that’s what campaigns normally achieve; terrific. You’ve got a very high-performing department. (It’s also a very positive result – since over 80% of marketers use campaigns mainly to increase sales.)
But if it’s 10% because the last three campaigns only managed 1% ... other questions emerge. Start with:
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Who are we talking to? Has this audience been approached before?
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How large is the audience? A mass market or a niche?
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What are we saying? Have we sent these messages in a past campaign?
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What happened last time? Did we achieve that 10% target?
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How long did it take? Did 95% of responses come in within two weeks?
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How many leads do we want? Would one good new customer cover it?
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How much revenue should it generate? Do the numbers make sense?
The right metrics can be surprisingly simple
When it comes to lists, an existing list will almost always perform better than a brand new one. If you’re campaigning to a completely new list, the main objective is to find out what happens, not achieve 10% - it’s more of a research project.
(Knowing the ROI of a new list is valuable data in itself.)
While looking at messaging, business data analysis can be easier than you think. For example, you could look only at subject lines of past emails. What words and phrases delivered higher openings and clickthrough rates?
A few simple numbers will help manage expectations. If your average response rate is 2%, that’s already good. (The Direct Marketing Association notes a 0.12% average for email, with 4.4% for direct mail.) While even a low response rate can deliver great results if 1 in 2 of the recipients become customers.
Marketing data analysis isn’t about numbers. It’s about the story behind those numbers.
Finally, remember your objectives are at the end of a sales funnel, not a single campaign. How long is the sales cycle (time between initial lead and first sale?) What revenue does the campaign need to add to your topline?
These numbers let you question any outlandish expectations – such as a new list of 3,000 needing to deliver £1m in sales this quarter. Setting you up to exceed expectations later. (In a survey, an incredible 47% of respondents gave "Measuring the success of a campaign" as their single hardest task.)
So if you’re setting business objectives for a future campaign, make sure you know where you stand today. Knowing which metrics to measure makes it win-win.
How to find those metrics
Discover how to find the metrics to set realistic objectives for your next campaign in this guide; Which metrics to measure