Your data is across multiple systems, in multiple data silos making key customer insights for marketing impossible. Majority of customer interactions happen during a multi-channel, multi-event journey. How can you create a unified view of customer activity and behavior, both from formal and informal interactions, and turn them into actionable insights?
And what if on top of those actionable insights you could take advantage of machine learning & AI to automate business processes?
- Stakeholder interviews to understand your business and marketing challenges with respect to customer data.
- Identify and document sources of your customer data (e.g. CRM, website, email service provider, POS, 3rd party apps etc.)
- Customer 360 profile creation process: How data is filtered, merged, and aggregated to create user profiles.
- Identify Audiences / Segmentation: How customer profiles can be segmented to create highly flexible targets for marketing campaigns or further analysis.
- How to activate Customer 360 and audiences through personalization campaign execution utilizing no-code visual workflows or exported to external marketing tools like an email service provider or website tag etc.
- High level roadmap and strategy
- For a holistic, 360-degree view of customer records that captures different types of data from across channels and systems, aggregates the data to put the important information up front and applies analytics to deliver personalized, engaging customer experiences.
- Financial Forecast (12 months)
- Forecast of increase in revenue over 12 months (E.g. increase conversion, traffic, customer retention, cross sell / up sell etc.)
- Forecast of reduction in cost (e.g. customer service, ad spend etc.)
- Forecast of increase in customer satisfaction (e.g. NPS score improvement)
Benefits of Customer 360 Data Management:
- Targeted Marketing & Personalization: Creating a unified view of customer data helps uncover behaviors and insights. Micro-segmentation, next best offers and recommendation models are only as useful as the data behind it.
- Churn Prevention & Customer Retention: Good data can model and predict churn, and the more data you can bring to bear on the model, the better.
- Proactive Care: Data empowers marketers to reach out to customers before they churn.