A smartphone company, 'Innovate Mobile,' analyzes customer reviews to guide product improvements. They currently classify each review as simply 'Positive,' 'Negative,' or 'Neutral' based on the overall tone. They are puzzled by the feedback for their latest model, the 'Photon X,' as a high number of reviews are classified as 'Neutral,' providing no clear direction for the engineering team. Below are two typical 'Neutral' reviews they have collected:

Review 1: 'The camera on the Photon X is absolutely stunning, the best I've ever used. However, the battery barely lasts half a day, which is a huge disappointment.'

Review 2: 'I love the sleek design and the vibrant screen, but the user interface is slow and buggy, making it frustrating to use for daily tasks.'

Based on these examples, analyze why the company's current method of classifying entire reviews with a single sentiment label is failing to provide actionable insights. What specific, conflicting pieces of information are being obscured by the 'Neutral' classification?