These workflows aggregate product reviews into our database and then feed them into ChatGPT in order to get a concise, bulleted list of positive and negative feedback for you to review.
In this example, we’re using the Okendo reviews API to summarize reviews for a brand called Carnivore Snax.
Here is an example of the summary:
- Many customers love the taste of the snack, with frequent descriptions such as “flavorful,” “delicious,” “melt in your mouth,” and “addictive.”
- Customers appreciate the high-quality, lean protein content of the snacks and regard them as beneficial for their diet and lifestyle.
- The texture of the snacks is often highlighted as satisfying and the right balance of crisp, chewy, and fatty.
- The snacks are perceived to be worth their cost due to their high quality and taste.
- Some customers mention the benefit of ideal fat and protein ratios and the overall nourishment provided by the snacks.
- Some reviews highlight the versatility of these snacks, suitable as quick bites or as meal replacements.
- Some customers enjoyed the simplicity of the ingredients and respect the company’s mission to deliver healthy and nutritious snacks.
- Many customers also mention that they keep reordering due to the overall quality, taste, and convenience of the snacks.
- Some customers found the snacks to be too greasy, leading them to wipe them down before eating.
- A few customers mentioned dissatisfaction with the texture of the snacks, with complaints about them being too hard, dry, or chewy.
- Some found specific flavors or cuts of meat not to live up to their expectations, and that certain snacks had more fat than they preferred.
- The price of the snacks was a point of contention for some customers, with some feeling that they could be costly for regular consumption.
The first workflow saves the reviews:
And the second workflow pulls the reviews from the database and passes them over to ChatGPT for a summary:
We watch for new apps then package them into an email sent every Tuesday.