The first step of our customer analytics process is to extract the data from the survey which broadly consists of satisfaction scores across all rating questions, and demographic data along with the open text feedback.
Then we do the data cleansing to focus only on the survey questions that drive customer satisfaction.
We map the customer journey with each question of the respective business KPI.
We use methodologies such as text analytics (NLP) and sentiment analysis to get the overall impact on the NPS across the customer journey stages.
The third step is to integrate your data with visual analytics to capture non-obvious insights.
We record the impact of satisfaction analysis by visualizing trends in the customer journey rankings.
Then, we weave every insight into a story to derive decisions to improve customer satisfaction scores.
Final stroke. Get out of the code-intensive data applications and reap the benefits of Gramex, a low-code development platform that rapidly connects to any data source and massively reduces time to derive insights.
Greens are Great. High Impact on Satisfaction and good revenue uplift
Reds are Fatal. High impact on Satisfaction but low sentiment
Ambers are potential risks. Low on impact but are low on revenue too
Greys are irrelevant. High impact but don’t impact the revenue by much