Thursday, May 20, 2021

Change Does You Good: Experience Evolution and Always-On Measurements Enable Quick Strategic Shifts

Kathleen Lukasik, Group Director – Analytics and Insights
Strategy / Data

Throughout the past 14 months, we have witnessed consumer behaviors changing at a pace that has never been seen before. We saw brands reacting these changes in a variety of ways, such as by shifting ecommerce strategies or launching new content on channels that were less topical prior to the pandemic. These brands, who successfully adapted and reassessed options to quickly find themselves on customers’ minds, were able to adjust to this rapid change and continue to meet customers where they are – and have been seen as innovative and adaptable to the ever-changing world around us.

 

Just as the complete disruption in March 2020 forced brands to rethink strategies, as the world continues to adjust to a newer-normal currently, brands must be able to understand customer wants and needs in order to overcome any obstacles and maintain relationships between the brand and its consumers. From our vantage point, we witnessed that most brands were not prepared to evaluate options and execute fast shifts, and those who did were relying on their agility to understand consumer behaviors and make quick changes.

 

This is a challenge Rightpoint has continually faced by implementing “Experience Evolution” strategies that reconfigure themselves as new information is gathered. We help clients navigate unchartered territory to adapt consumer behaviors to rapid change through insights and analysis.

 

Change is continuing, as evidenced by recent data by eMarketer finding that between January and April of 2021, the number of customers comfortable with shopping in-store rose from 47 percent to 69 percent, with “eating in restaurants” growing from 35 percent to 62 percent and “traveling/vacationing” more than doubling—20 percent to 44 percent. These trends have implications to strategies set last year and the need to proactively identify and react as needed.

 

Here’s more on how Experience Evolution ensures you’re collecting the right kind of data and sorting it under the proper guidelines, as to maximize effect­­­­:

What is Experience Evolution with analytics and insights?

The ongoing use of insights from data analysis and interpretation to inform and adjust the customer experience overtime is what we refer to as Experience Evolution. As a product and customer experience changes overtime, the ability to understand and react is imperative to the customer relationship, and ultimately value, with your brand.  

 

Readying your organization for the next phase of Experience Evolution can be a daunting and time-consuming process without the right expertise to tackle it. To get there, there needs to be a plan in place for the ongoing use of data points—such as digital product, website or in-store transactions—to guide that knowledge base. This affords the ability to proactively identify shifts in KPIs aligned to the customer experience with a brand, interpret those findings and react in an agile method.

Data Identification and Collection

To prepare for ongoing analysis of a customer experience, consider what the aperture is for the work you’re doing. Is your brand focused on a singular DTC digital channel, or do they have a multi-channel relationship with the customer? Next, identify for each channel what data is available and how it is collected. Consider additional relevant data sources, such as how COVID-19 regulations are shifting, on which to model behavioral change, and ensure you’ve put a solid data structure in place.

 

This step is of paramount importance, especially considering many organizations haven’t gotten the memo. To date, according to eMarketer, one third of organizations do not understand how to get their hands on this data, or how to take advantage of or own the data to get to useful, let alone ongoing, results.

Establish a measurement framework and learning agenda

A robust collection of data is not enough in and of itself. You need to develop a measurement framework and learning agenda for how to activate the data. Essentially, the measurement framework and learning agenda provide a blueprint for analytics in the future. 

 

Proceed with caution, though. Remember to not specifically look just at KPIs in a framework, but rather build out layers of analysis that will allow you to get to the contextual triggers of behaviors. It’s important to be able to uncover insights through exploratory analysis, be it by audience or acquisition source, for a true understanding of insights that matter. 

 

A framework should consider both qualitative and quantitative methods to bring together insights. While qualitative learnings may be at a less frequent cadence, it helps keep a pulse on consumer wants/needs, while very frequent quantitative analysis can identify trends and patterns to ease the speed by which you can react.

 

Finally, the ability to react to rapid change rests on an approach to measurement and insights that is always on, identifying what customers want in that moment through analysis determines how best to adjust. Just as a finance organization will frequently consolidate financial statements, you don’t want to be too far removed from understanding the shifts in customer experience data before something changes drastically. If you do not consistently measure performance, you will likely lose opportunities and, most importantly, customers.

Meaningful analysis for the data end-user produces outcomes

Data strategy continues to become more relevant as organizations try to sift through the massive amounts of data they have begun to gather over the years. Rightpoint ensures measurement approaches align to the organization in order to provide meaningful insights, compared to a plethora of data points without action. 

 

To do this, when establishing a measurement approach, we must consider the end user of the data. Move beyond why we need to look at data—which can end up being confusing and unusable—to how different roles in the organization will use it in their day-to-day.

 

Activating insights at the right level, and to the right audience, will allow your organization to better adapt to the situation. Data points and trend lines alone do not explain “what.” As mentioned previously, deeper analysis is necessary to uncover insights and recommendations that can be activated. Depending on the organization and maturity of data use, an analytics framework will look vastly different. 

Activate, monitor and adjust strategy

An always-on approach to measurement can incorporate a variety of analytics techniques including performance measurement, testing strategies and behavioral analysis. As an analytics framework is set in place, Rightpoint begins to structure, analyze and interpret data in order to monitor shifts and dig into the reasoning behind the results. Results and insights from data analysis should be wide-reaching, bringing in multiple POVs, to uncover as many opportunities as possible.

 

Remember that creating a framework for always-on analysis is not a one-time engagement, nor involves solely analytics team members. As we start to learn and adjust KPI’s will need to be revisited, the digital channels updated, and content created to ensure you are creating the optimal customer experience that is founded on the use of data and insights. As insights become an integrated part of the work in your customer experience strategy, you will be able to overcome rapid change obstacles with agility and will be ready to react to whatever the future brings. 

 

Interested in learning more about Experience Evolution? Get in touch today to learn more.