Sales Filter X AltViz
The highlights of our October webinar for CXOs in Retail.
The webinar focused on the burning questions retailers have around the trends and challenges of automation and advanced analytics, and the power of CMX to find profit in the data from their business.
Who are AltViz?
The technologies we deploy to help businesses make faster and better decisions for their company
Our growth as a VC-backed business
The type of work we undertake, for example with our largest customer eBay where we process 40 million listings every two hours in our cloud environment
Key Technology Trends In Insurance & Retail
Key Trends In Insurance
Unstructured data processing for P&C insurers, including call handler monitoring and enhanced compliance
The agenda of CXOs spurred on by Insurtech
The rise of RPAs and the challenges of legacy system integration
Key Trends in Retail
Upgrades to core ERPs
The drive to speed up decision making
Operational automation (with customer-facing and customer-driven automation examples from Amazon, Tesla and Walmart.)
CMX, The Use Cases For Advanced Analytics
How CMX translates complex data into the context of an employee's day-to-day job for faster and/or automated decisions
How CMX is not a SAAS product (and the implications for improved security)
A real world example for retailers, looking at how CMX helps a retailer to react to unexpected events such as changes in weather.
Who Can Find Value In CMX?
Examples from our current conversations include:
A global consumer electronics brand, where CMX could play to its strengths of handling a large sku portfolio within a global omnichannel strategy
A large fresh foods brand whose customers are supermarkets, with the pain point of a lengthy sales process but very short order lead time.
In the FMCG sector, a global confectionery company looking to improve planogram compliance.
What Are The Integration Challenges For Retailers?
Exploring the principle challenges including:
How AltViz approaches integration: starting small, scaling out.
The downstream integrations, e.g. with communications tools such as SMS or Slack
Why our containerisation of CMX is better for security and for controlling data access
The learning curve for business users
How Does CMX Use Machine Learning?
How companies can profit from ML by using CMX to move processes stage by stage from manual, human actions to automated ones
A real world example of how AI can structure previously unstructured data to give meaningful insights
How CMX uses ML to validate and sensecheck thresholds set by humans