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Outlier 2022 Predictions: Reimagine and Rebuild - Three Changes Companies Will Make to Keep Pace with Consumer Behaviors in 2022

vmblog predictions 2022 

Industry executives and experts share their predictions for 2022.  Read them in this 14th annual VMblog.com series exclusive.

Reimagine and Rebuild - Three Changes Companies Will Make to Keep Pace with Consumer Behaviors in 2022

By Mike Stone, CMO, Outlier

Much has been said about whether companies will ever recover from the market disruptions experienced over the last 21 months. But as consumer behaviors continue to evolve, we need to change the conversation. It's no longer about business recovery - it's about reimagining and rebuilding.

Companies are trying to keep pace with changing patterns, but how consumers research, buy and recommend products continues to be a moving target. Previous buying behaviors and forecasts are no longer relevant, and data that once provided guidance to drive business decision-making is less reliable.

In order to be agile to meet changing consumer demands we must reimagine all areas of engagement. And to rebuild just-in-time marketing programs, manage inventory across all buying channels and create consistent revenue streams, we need to narrow in on real-time behavioral models.

The companies that understand and elevate changes in behaviors and data in real-time will be the ones that succeed in times of rapid, uncertain change. Here are three steps companies will make in 2022 to begin the process.

1.       Empower enterprise-wide data-driven decision making

Consumers will continue to move online forcing consumer brands to continue to increasingly shift business models to digital channels. This provides companies with an incredible amount of data related to customer behaviors, including e-commerce, social and web data, and data from stores and the supply chain such as POS, inventory and returns. Many organizations are still working with siloed data only available in standalone systems or to certain individuals. This makes it difficult for companies to identify the most valuable data and which changes occurring in the data are relevant to their business, sales and marketing activities. 

Creating a 360-degree view of customer behavior requires analytics to cut across each of the different, siloed data sets. And sharing that data across the enterprise in an easy-to-understand and digestible format is required. For decision-makers to leverage the data they need, when they need it, means that companies will look at how they can democratize their data moving forward.

There are two key elements of true data democratization. The first is the ability to integrate or connect multiple data-collection systems, whether that's web traffic, marketing campaigns or product inventory, so that all data becomes part of any data analysis.

The second requires broad sharing and visualization of that data in a manner that allows everyone across the organization, regardless of technical or analysis capabilities, to be able to understand and use the data for actionable decisions. A cohesive view of data that elevates important changes in data or behavior allows different decision-makers to quickly pinpoint problem areas relative to their roles and take action to improve everything from inventory, to manufacturing to marketing and customer experience.

2.       Embrace tools that provide deep data insights

Once organizational teams have access to all the data needed, they then need to be able to analyze the data to best understand their consumers' behaviors. Many traditional business intelligence tools and dashboards often lack the timeliness of delivery and deep insights. This puts pressure on the organization to have analytics talent, which most lack, in order to go beyond top-level data to make immediate, data-driven decisions.

To overcome this, companies will turn to software solutions that deliver deep insights in a way that is understandable, digestible and actionable. Insights tools give companies a more complete view of what is happening in relation to different data sources such as e-commerce sales, stores sales, digital campaigns and inventory. Enabling teams to guide strategy, campaigns and forecasting by delivering outcome-driven models across data sources, alerting them to trends and allowing them to run basic simulations.

One tool that can help teams automatically analyze and act on unexpected changes in data collected by analytics tools is called automated or augmented business analysis. Automated analysis tools can elevate even subtle changes in unexpected data behaviors, which means that teams don't need to know which questions to ask of their data. Alongside the business intelligence dashboards that are already tracking predetermined KPIs, automated analysis tools can identify and flag just the relevant changes, letting decision-makers know exactly where to look and why. With automated business analysis, companies can gain a competitive advantage by going beyond top-level data to fully understand the story it tells and make data-driven decisions to align with the changing consumer.

3.       Increase frequency of data analysis

Consumers experimented with many new ways of engaging with brands over the past 21 months. In fact, consumers successfully shifted entire markets such as grocery and retail to reimagine customer engagement, delivery, service and loyalty. For many companies, this means that the old approach of customer segmentation, forecasting and pre-planned campaigns is no longer effective.

To keep pace with changing consumer behavior moving forward, brands will need to increase the frequency of their data analysis. Data democratization and embracing tools that deliver deep data insights are the first steps companies can take to start viewing their data more timely. Once companies go from analyzing data on a monthly or weekly basis to a daily basis, they will be able to quickly pivot business, sales and marketing activities to know immediately when they need to act on customer behavior changes.

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ABOUT THE AUTHOR

Mike Stone, CMO, Outlier

Mike Stone 

Mike Stone is the CMO at Outlier.ai, responsible for the company's market growth strategy, demand generation, communications, product marketing and inside sales. For over 20 years, Mike has led marketing organizations and provided strategic consulting to technology companies. Most recently, Mike was SVP of Marketing for Airship, the leader in mobile customer engagement. Prior to that, Mike led marketing for Salesforce Community Cloud-from its initial launch through four years of dramatic worldwide growth.

Published Wednesday, January 26, 2022 7:32 AM by David Marshall
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