Sentiment Analysis for Customer Feedback: Understanding Your Users

Voice of the Customer at Scale

Manually reading thousands of reviews is impossible. Sentiment analysis automatically categorizes feedback, identifies trends, and surfaces critical issues requiring attention.

Basic Sentiment Analysis

class SentimentAnalyzer
{
    public function analyze(string $text): array
    {
        $prompt = <<ai->generate($prompt, ['temperature' => 0]), true);
    }
}

Batch Processing Reviews

class ReviewAnalyzer
{
    public function analyzeNewReviews(): void
    {
        Review::whereNull('sentiment_analyzed_at')
            ->chunk(100, function ($reviews) {
                foreach ($reviews as $review) {
                    $analysis = $this->sentiment->analyze($review->text);

                    $review->update([
                        'sentiment' => $analysis['sentiment'],
                        'sentiment_score' => $analysis['confidence'],
                        'aspects' => $analysis['aspects'],
                        'sentiment_analyzed_at' => now(),
                    ]);
                }
            });
    }
}

Trend Detection

class SentimentTrends
{
    public function getWeeklyTrend(string $productId): array
    {
        return Review::where('product_id', $productId)
            ->whereBetween('created_at', [now()->subWeeks(4), now()])
            ->selectRaw('
                WEEK(created_at) as week,
                AVG(CASE WHEN sentiment = "positive" THEN 1 ELSE 0 END) as positive_rate,
                COUNT(*) as review_count
            ')
            ->groupBy('week')
            ->get()
            ->toArray();
    }

    public function detectIssues(): Collection
    {
        // Find sudden increases in negative sentiment
        return Product::all()->filter(function ($product) {
            $recent = $product->reviews()->recent(7)->avg('sentiment_score');
            $baseline = $product->reviews()->recent(30)->avg('sentiment_score');

            return $recent < $baseline - 0.2; // 20% drop
        });
    }
}

Alert System

class SentimentAlerts
{
    public function check(): void
    {
        $issues = $this->trends->detectIssues();

        foreach ($issues as $product) {
            Alert::create([
                'type' => 'sentiment_drop',
                'product_id' => $product->id,
                'message' => "Sentiment dropped significantly for {$product->name}",
                'data' => $this->gatherContext($product),
            ]);
        }
    }

    private function gatherContext(Product $product): array
    {
        $negativeReviews = $product->reviews()
            ->where('sentiment', 'negative')
            ->recent(7)
            ->get();

        return [
            'common_complaints' => $this->extractCommonIssues($negativeReviews),
            'sample_reviews' => $negativeReviews->take(5)->pluck('text'),
        ];
    }
}

Conclusion

Sentiment analysis transforms unstructured feedback into actionable insights. Combine automated analysis with trend detection and alerts to stay ahead of customer issues.