If we need to create a ‘generic case study’ (how somebody might use the techniques or ideas we’re describing), AI can be very helpful.
More playing around with ChatGPT content generation today. See what you make of this.
It’s always great to illustrate educational articles with real life case studies. Often however, it’s not possible to do this, because there’s no case study available. But when this happens, it’s a legitimate strategy to use a ‘generic case study’ – in other words, how somebody might use the techniques or ideas we’re describing.
It might seem odd to get AI to ‘humanise’ an article, but ChatGPT can be a big help here, creating a first-pass case study for us.
Here’s an example. Yesterday, I wrote a short piece suggesting that it might be worth looking at Microsoft Advertising alongside Google Ads. Could we illustrate this with a generic case study? I asked ChatGPT to read the article, then “make up a case study about how a typical user might advantage of this advice and the results they might obtain. Keep things generic, do not make up names, industries or specific results data.”
Here’s the response. I think it could easily be the basis of something that would have enhanced the article. As ever, don’t be too concerned about any questionable elements of what’s been written, as we can sort these out from our own knowledge of the subject. Just consider how long it might have taken to write this ourselves from scratch.
Case Study: Leveraging Microsoft Advertising for Cost-Effective Conversions
Background:
A business running digital marketing campaigns was experiencing diminishing returns on its Google Ads efforts. Initially, the company had seen strong performance with conversions costing around £10 each. However, as the campaign matured, the more effective ad placements were becoming saturated, leading to an increase in the cost per conversion, with some ads costing as much as £15 to £20 per conversion.
Looking for ways to optimize their ad spend, the business decided to explore Microsoft Advertising as an alternative platform to complement their existing efforts on Google.
Challenge:
The primary challenge was to maintain or reduce the cost per conversion while continuing to drive a high volume of quality leads. The business needed to find a way to use its budget more effectively, particularly for conversions that were becoming increasingly expensive on Google Ads.
Strategy:
Based on the advice that Microsoft Advertising could offer a more cost-effective solution, the business decided to allocate a portion of its ad budget to this platform. The following steps were implemented:
1. Budget Diversification: The business reallocated funds from the less effective Google Ads placements, which were costing £15-£20 per conversion, to Microsoft Advertising, aiming to achieve conversions at a lower cost.
2. Utilizing LinkedIn Profile Targeting: One of the key features of Microsoft Advertising that the business leveraged was the ability to target ads based on LinkedIn profiles. This allowed for more precise targeting of professional demographics that were likely to convert, aligning with the business’s ideal customer profile.
3. Custom Ad Copy: The ad copy was tailored to resonate with the professional audience targeted through LinkedIn, emphasizing the value propositions that were most relevant to this demographic.
4. Performance Monitoring: The business closely monitored the performance of their Microsoft Advertising campaigns, making regular adjustments to bids and targeting criteria to maximize efficiency and return on investment.
Results:
As a result of implementing Microsoft Advertising:
– Cost Efficiency: The business was able to secure conversions at a lower cost compared to the more expensive Google Ads placements, effectively bringing down the overall cost per conversion.
– Improved ROI: By targeting a new audience segment through LinkedIn profiles, the business saw a noticeable improvement in the quality of leads, contributing to a better return on investment.
– Diversified Traffic Sources: The business was able to diversify its traffic sources, reducing dependency on a single platform and spreading risk across multiple channels.
Conclusion:
This case study illustrates how a business can effectively use Microsoft Advertising to optimize its digital marketing strategy. By reallocating budget from less effective Google Ads placements and leveraging unique targeting features like LinkedIn profiles, the business was able to achieve more cost-effective conversions, improve ROI, and diversify its online presence. This approach highlights the value of experimenting with different advertising platforms to find the most efficient use of marketing resources.
Give this a go on any article you have in your own market sector which seems a little dry, and which could use a more human angle. The results can be surprisingly good.