Over the past decade the big data hype cycle has taught us that while data is important it’s not necessarily its size but its value that matters. We get value from data by discovering insights based on desirable outcomes and taking action on them through 1:1 customer decisioning.
Closing the loop means we have to first create data that represents the communication between systems across these functional areas:
- Customer decisions
- Customer interactions
- Customer conversion
How many systems will depend on your organization, your industry and the digital channels available to your customers. We’ll track these customers’ data across these channels through to outcomes that serve strategic organizational objectives. This data is the electronic data record of your wins and losses with your customers and is highly nuanced by customer, interaction, channel, campaign, offer and outcome.
With system and data integration in place our next task is to effectively wield this data capability. To do so we must solve for Insight Latency. Insight latency is the speed at which the organization can discover a customer insight, take action and measure effectiveness in the context of a strategic customer outcome. When an organizations’ Insight Latency is faster than the rate of the underlying customer behavior changes then you’ve successfully closed the loop.
Rate of Change (Insight to Action) > Rate of Change (Customer Behavior)
There are several factors that contribute to the time, cost and complexity associated with solving the Insight Latency equation. Traditionally, the most severe factor is the overwhelming presence of human labor.
This is where Toovio leverages AI and data automation to two areas of work that traditionally would have been performed via human labor:
- Modeling
- Measurement
In our decades of experience closing the loop for organizations these two areas are chock full of time, cost and complexity. So, we have been focusing our methodologies and our AI solutions on virtually eliminating human labor from modeling and measurement so the human marketers and analysts can spend their time and focus on defining outcomes aligned with strategic objectives.
Closing the loop first means system and data integration. Then we wield this data to drive a specific outcome. Finally, we extend and scale the outcomes we want to drive with human domain expertise against organizational strategic objectives. This iterative approach gets smarter and more impactful with each progression.