A. Salama

FREQUENTLY

ASKED

QUESTIONS

How to AI/DATA ANALYTICS will help my business?

AI and analytics uncover hidden patterns in your data to drive decisions from predicting customer churn to optimizing operations. For example, During my engagement with Lexus’s aftersales division, our analysis revealed a critical insight: 25% of high-value customers were not renewing their service contracts after expiration. We designed a targeted campaign with personalized offers for these high-potential customers, resulting in a 13% increase in quarterly profits.

2. Do I need clean data to start?

No, we clean and structure raw data as part of our process. In fact, 80% of our work is data prep. Share what you have, and we’ll handle the rest.

3. How do you measure success?

With KPIs tied to your goals: During my consulting engagement with VOIS's customer service division, a persistent rise in call abandonment rates (KPI) caught our attention an issue initially dismissed as seasonal fluctuation. Our detailed analysis revealed a deeper problem: a 22% increase in abandoned calls (KPI) over three months, directly tied to an undetected system flaw in call routing that created frustrating delays for customers.
We immediately presented these insights to leadership with a clear link to revenue impact, prompting swift action. Collaborating with IT, we optimized the call routing system, cutting wait times by 40%. Simultaneously, we implemented targeted agent training to improve peak-time handling.
The results were transformative: within 30 days, abandonment rates dropped by 15% (KPI), customer satisfaction (KPI) scores jumped 18%, and social media complaints (KPI) noticeably declined. This initiative not only resolved an invisible operational drain but became VOIS's new standard for proactive service monitoring across all regions.

4. How do we maintain results after the project?

We provide:
Training for your team
Automated reporting tools
Optional retainer supportSo you keep extracting value long-term.

5. Can you explain technical results to non-technical teams?

Absolutely. We translate ‘model accuracy scores’ into plain English: ‘This predicts customer behavior with 92% confidence here’s how to act on it.’

6. How do you ensure data quality in your analyses?

Poor data quality costs businesses an average of 15% of revenue (Gartner). We implement rigorous validation processes to ensure your data remains accurate, complete, and reliable at every stage.

7. What if we lack technical talent?

Totally Fine 😄, We've empowered managers across diverse industries with simplified troubleshooting techniques and quick-reference solutions, supported by complimentary documentation for seamless implementation.