I started ASAPP to build machine learning (ML) products to solve large enterprise business problems that share three attributes: they are economically massive, are systemically inefficient, and contain large amounts of data. Simply put, these are problems worth solving.
After a particularly bad call with my cable provider that lasted nearly three hours, I landed on the problem of customer experience, specifically how large organizations interact with their customers through contact centers. It checked all the boxes: hundreds of billions of dollars in annual spend, antiquated technology that perpetuated inefficiency, and large amounts of data. In addition, study after study has found a direct correlation between positive customer experiences and customer lifetime value (I ended up switching cable providers).
In the wake of the current pandemic, many of us have experienced firsthand just how broken customer experience operations are. The massive increase in inbound call volumes, coupled with reduced agent availability due to shelter-in-place policies, has exposed how Fortune 500 contact center organizations are fragile and incapable of serving customers when it’s most needed. All of the enterprise customers we serve have seen a 200%-900% increase in call volumes, with an average 50% decrease in agent availability. (One airline customer experienced a week with 26 times its average call volume!) Wait times are unbearable, customers are frustrated, and agents – dealing with the volume and frustration while trying to adapt to new working conditions – are increasingly overwhelmed.
Where are the digital tools that promised to help contact centers scale?
Over the last 20 years, contact centers have spent billions and billions of dollars investing in technologies explicitly designed to keep customers away from agents. This has led to misguided “success” metrics like customer ‘containment’ and ‘deflection’ — and a lot of miserable customers. These technologies were sold with the promise of agent elimination. Yet the agents are still here — in massive numbers. Many Fortune 500 consumer companies spend $1B or more in costs associated with agents alone. With the technology industry so focused on keeping customers away from agents, the agent experience has been devoid of any innovation.
Agents — the people on the frontlines serving customers, are themselves not being served with the technology they need to do their job effectively. Instead, they’re stuck using outdated technology, most of which was architected back in the ’90s.
ASAPP brings innovation to the most expensive (and essential!) aspect of customer experience – the human agents. By augmenting and automating workflows, we increase agent throughput by 5X or more — while making them happier and giving customers exactly what they want – personalized, high-quality experiences across any channel. For the first time, companies don’t have to sacrifice high-quality experiences in the name of cost-saving measures.
ASAPP delivers radically better outcomes by taking a radically different approach. Research and development are core to everything we do, and nearly 80% of our team members are part of our R&D organization. This team includes top scientists across multiple AI disciplines, such as natural language processing, machine learning, and speech recognition. Our team members join ASAPP because of the opportunity to have an impact not only on the development of novel technologies but also by building applications that can bring new solutions to the significant problems we are tackling for our customers.
Leveraging machine learning to make us more productive than we ever thought possible is one of the major imperatives of our generation. For ASAPP, focusing on building products that deliver operational transformation to large enterprises allows us to tackle this opportunity head-on, in a way that can result in a radically more efficient world. We are just beginning to scratch the surface of what’s possible, and I’m proud of the work the ASAPP team will increasingly play in making this dreamed future a reality.