How Automated Business Analysis Can Help Marketers Adapt to Shifting Consumer Behaviors
With pressure to optimize sales in the wake of the pandemic, retail marketers are looking to real-time customer, commerce and market data to accommodate changing buying behaviors and capitalize on growth opportunities. A recent study collected insights from leading retail brands to determine how well they gather, integrate and leverage data to personalize marketing and branding efforts.
The study found that over 70 percent of retail companies with access to large volumes of business data continue to be surprised or blindsided by changes in customer behavior, processes or preferences.
And despite all the data, 73 percent of retailers don’t feel like they can spot trends or anomalies in their data that could lead to helpful business decisions. In addition, 44 percent of those that use data regularly report that they're unable to find valuable or relevant trends within the data.
Hurdles Impeding Meaningful Customer Insights
Customer insights lie at the core of improving the precision and speed of digital marketing efforts. However, retailers struggle to get actionable insights for three core reasons — a lack of data integration, a lack of timely insights, and a lack of analytics talent. Across the board, retailers are capturing more data than ever before, but over 70 percent are unable to integrate data from multiple sources, and more than 65 percent are challenged with getting insights fast enough to act on the data.
As amounts of data continue to grow, the analytics talent needed to translate raw data into simple recommendations is limited. An astounding 70 percent of retail marketers say they don’t have sufficient analyst support to provide the insights they need. In fact, only 11 percent of retail teams have a dedicated analyst to help make sense of marketing campaign performance and customer behavior data. Therefore, it’s no surprise that they also report an inability to pivot marketing programs in a way that allows them to capitalize on sales opportunities.
Without the right insights, retailers are flying blind when it comes to optimizing marketing ideas and spend. This is spiraling into missed opportunities and wasted efforts, such as potential missed sales, promotion out-of-stock items, underperforming marketing campaigns, and misalignment of marketing spend.
According to the study, 79 percent of retail marketers made substantial changes to digital marketing strategies in 2020 in response to market changes. However, few of these changes were informed by meaningful data — most were reactive, based on limited data or gut feel. In fact, nearly half reported they weren't using any data to inform changes to their digital marketing strategy at all, and only 33 percent thought they had sufficient data to inform decision making.
Improving Precision and Speed of Customer Insights
As changes in consumer behavior are expected to persist, it's imperative that retailers leverage data the right way to inform marketing strategies on an ongoing basis. For companies to improve the precision and speed of customer insights, they require teams to focus on three pillars:
- Data democratization: Retailers should adopt modern analytics platforms that allow for easy integration of multiple data sources, and provide ongoing and automatic analysis of new data.
- Actionable analytics: Traditional dashboards lack timeliness of delivery and deep insights. Retailers must go beyond top-level data to make immediate, data-driven decisions. This requires embracing software that serves up just the relevant insights, without all the clutter.
- Support structure: Retailers will continue to lack comprehensive data analytics support on their teams. Instead, they should rely on smarter tools that can lessen the burden by quickly delivering automated, curated insights across all marketing data.
By keeping these pillars in mind when evaluating new tools for automated analytics, retailers will set themselves up for success. As companies strive for complete digital transformation, they can leverage existing data infrastructure and easily layer automated analytical tools on top of current solutions. This, in turn, will create an agile environment that leverages the combined strengths of technology and human analysis, allowing retailers to automatically monitor large volumes of data, and quickly identify and elevate segments of data that point to problems or opportunities in the business. By empowering marketing, sales, supply chain and other teams with data, changes in consumer behavior may continue, but business strategies can finally hit the mark.
Mike Stone is the chief marketing officer at Outlier, a business analysis tool that utilizes the latest in artificial intelligence within its data analytics platform to identify data outliers.