In a sector that is hyper-aware of the importance of an evidence based approach, data has become near-essential to include as proof points for the promotional statements that we make in the marketing pieces we produce for our clients.
It is obviously vital to ensure that the stats and facts that we include are not only accurate but also representative of the point being made. Clumsily trying to shoehorn data into marketing messages can risk the final statements being a bit lacklustre or worse still, make it impossible for the data to be used at all when marketing messages are very specific.
Finding compelling sales arguments in market or scientific research can sometimes just be a case of looking at things from a different perspective though. Here are a few of the tricks that we use to ensure that data remains representative and accurate but exploits all of the commercial benefits:
1. Re-represent stats
Sometimes it’s as simple as changing the way you say something. 1 in 3 can sound much stronger than 33%, for example.
2. Reverse stats
Often useful with market research data, when [low percentage] of respondents said they did, it can mean that 100 minus [low percentage] of respondents said they did not. Being able to do this is often dependent on how the question is worded but can provide a much stronger statistic.
3. Combined response stats
This one is really useful when the answer selection is provided as a range. For example, if 54% of dog owners said something was difficult and 21% said it was impossible, it allows the statement “75% of dog owners thought it would be difficult or impossible…”, which sounds much more compelling.
4. Blended stats
This has to be done carefully to remain representative but it is sometimes possible to take two unrelated stats and combine them to create a new one. For example:
- The reason for 20% of pet dog vet visits in the UK is because of disease X.
- 50% of UK dog owners think the treatment for disease X is dangerous.
Final statement: As many as 1 in 10 dog owners that a vet sees will think the treatment protocol advised to them by their vet is dangerous.
Information or demographic crossover (in this case, both UK based and dog specific) plus specific details (only dogs visiting the vet, rather than overall disease prevalence) helps build the final statement but phrases such as ‘as many as’ or ‘up to’ helps to mitigate against the unavoidable different variables, while still maintaining data-use integrity.
Can we help find the commercial angles in your data? Get in touch: firstname.lastname@example.org