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How automated data analysis enables collaboration between marketing and IT
In the last few months, consumers’ shopping behaviours have changed more rapidly than any projections. Consumers have completely embraced digital channels during lockdown and they have grown expectations that brands unite their offline and online experiences.
When the consumer world undergoes such seismic changes, marketing teams have to respond.
In the report CMO Priorities in Light Of The Pandemic Crisis Forrester recommends that CMOs focus on the following short term priorities:
- Revise placements and content to create the value that customers need now
- Fix common customer experience problems
- Audit services and technology partnerships for possible cost savings.
Being both a savvy digital consumer and a marketer I’m very interested in how consumer brands tackle the challenge of fixing customer experience problems.
I’m a big fan of experiential marketing, an approach that has actually been around for 30 years. The first examples of experiential marketing came out between mid to late 1990s when we first heard of concepts like the Rainforest Café and when the Ritz-Carlton Hotel moved from a service to an experiential orientation.
The pivotal idea is to give customers a unique experience, like dining in the rainforest, that they would remember, they would talk about and make them want to go back.
Since then, the term has been commoditised. It has been associated with the delivery of a fast and efficient customer journey - including elements of personalisation and shopping recommendations.
Now, consumers expect a single, consistent, personalised experience, anywhere and anytime. Brands can’t afford to create barriers that disrupt customer satisfaction - or don’t cater to what the customer wants.
So, what are the main problems marketing teams have when they’re trying to fix customer experience problems?
There are too many steps in the delivery process and too many touch points that don’t fall under the direct responsibility of Marketing.
- Stock management - having the product available that customers like. Whenever they want it;
- Device issues - anything from problems with payment systems to the app that can’t find the customer’s location;
- Website stability issues - customers not purchasing because the site is down either before the customer reaches checkout, or goes down during the transaction.
- Unattractive purchasing journey - customers finding that buying the product or service takes too long is too complicated or both!
The list of things that could go wrong runs into miles - and the road ahead is dark and foggy.
The problem is that marketing teams don’t have overall visibility of all these variables and components that form the substrate of customer experience. I’m sure IT, Operations and Product teams, just to name a few departments, all collaborate with Marketing to ensure that their company delivers the promise that the brand makes to customers.
But what if, in order to lower barriers to customer satisfaction, we could create a synergistic link and facilitate the collaboration?
What if Marketing, which ultimately is the team accountable for the success or failure of customer experience, could get full visibility of all of the data that map the customer journey?
What if marketers could be immediately notified when a problem occurs that might negatively impact on customer experience?
What if marketers could also understand the root cause of the problem in seconds so that they can proactively tackle the problem before it becomes an issue and avoid negatively impacting customers?
I believe that anomaly detection and root cause analysis can make all of the above possible.
For many years we have rested on our laurels - relying on dashboards to tell us what’s going on in the business. And while this type of reporting is still great at showing high level trends, it lacks that always-on monitoring and metric explainability that machine learning can deliver. For modern marketers simply monitoring revenue and customer retention rates is not enough.
If you are focused on customer engagement, you now need to consider an automated data analytics solution that
- Allows you to map your customer journey
- Alerts you of any problems that might arise in course of the customer journey
- Helps you to quickly identify why, so that you can fix the problem before it becomes an issue and negatively impacts your customer experience.
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