Fusion360 Overview
Turn fragmented customer data into revenue-generating customer intelligence. Start quickly, prove value through focused use cases, and scale without beginning with a large transformation project.
Most businesses are not short of customer data; they are short of context. The same customer appears in POS, e-commerce, CRM, loyalty and campaign tools with no shared identity, so marketers guess instead of acting. Fusion360 restores that context - one profile per customer, enriched with behaviour and predictions - and turns it into hyper-personalised engagement, real-time segmentation and measurable ROI, live in four weeks.
43%
report poor data quality as the major blocker to omni-channel goals
Source: HBR
70%
struggle with disconnected data silos across online and offline channels
Source: Forrester
67%
say customer identity and a single customer view are not aligned to marketer needs
Source: Industry research
75%
struggle to meet ROI from a data-driven approach at reduced operating cost
Source: Industry research
Reported results
9%
Sales uplift
13%
Increase in wallet share
23%
Saved on marketing costs
Why clients choose Fusion360
- Built for all industries, with 300+ KPIs and customisable RFM segments.
- AI-powered insights, advanced transformation rules and NLP-based segmentation.
- Quick, marketer-friendly setup with a four-week implementation.
- Incubated at adidas and built by marketers for marketers.
Live in four weeks
- 1Ingest. Use built-in connectors to bring online and offline data in.
- 2Transform. Apply advanced AI-driven transformation rules to clean and enrich it.
- 3Create segments. Profiles build in minutes, enabling AI-based and NLP segmentation.
- 4Run campaigns. Activate personalised campaigns against those segments and measure revenue.
Before and after Fusion360
| Aspect | Before | After |
|---|---|---|
| Data unification | Months | Hours |
| Segment creation | Days | Minutes |
| Audience engagement | Low interaction | High interaction |
| Personalisation | Generic | Hyper-personalised |
| Marketing attribution | Months | Hours |
| Revenue impact | Below average | Above average |
Context talk track
- Customer data sits in separate systems: POS, e-commerce, CRM, loyalty, service desk, campaign tools and offline registers.
- The same customer appears several times under different identifiers, so no team can answer basic questions reliably.
- Marketing falls back on broad segments, and revenue opportunities such as cross-sell, repeat purchase and churn prevention are missed.
- Connect existing online and offline data sources without replacing current systems.
- Resolve identities so one customer becomes one profile across channels.
- Enrich each profile with transactions, engagement, preferences and predicted behaviour.
- Build audiences and push them to the channels the client already uses.
- Measure the business outcome of each activation and repeat what works.
- Businesses with a large base of identifiable customers and repeat-purchase potential.
- Teams whose customer data is spread across three or more systems.
- Marketing, CRM and business teams that need to act on data, not just report on it.
- More repeat purchases from existing customers.
- Higher cross-sell and upsell conversion from relevant offers.
- Lower churn through earlier detection of at-risk customers.
- Better campaign relevance and less wasted spend.
- A single, trusted view of the customer for every team.
- Start with one measurable use case and two data sources.
- Prove identity resolution and profile quality on real client data.
- Deliver one activation output per agreed use case.
- Review results, then extend sources, use cases and automation.
Key capabilities
| Aspect | Customer database | Actionable CDP |
|---|---|---|
| Purpose | Stores customer records | Drives customer action |
| Identity | Duplicates across systems | Resolved into one profile |
| Data | Mostly static attributes | Attributes, behaviour and predictions |
| Output | Reports and extracts | Audiences, journeys and activations |
| Ownership | IT-led | Business-led with IT support |
| Measurement | Data quality metrics | Revenue, retention and campaign outcomes |
