The new normal for household cleaning product purchases
This shift in household cleaning product purchasing habits corresponds with an uptick in overall household cleaner spend as a germ and Covid-free home environment became a top priority for consumers. As recently as this spring, Clorox reported that the company’s two-year stack growth remains robust and well above pre-pandemic levels. This bolsters the “new normal” argument—that growth in spending categories like household cleaners and other products used to clean and disinfect—will stay consistent even after markets recover from the pandemic.
Motivated to avoid or limit exposure, many consumers shifted to online as opposed to brick-and-mortar shopping experiences. And yet, in specific instances, brick-and-mortar basket spend increased too. For household cleaner manufacturers, knowing where their shoppers bought their products, how much they spent, how often they spent it, and what age group did the spending is key to understanding this “new normal.” Also important is knowing the ratio of online to brick-and-mortar, and whether the online channel is cannibalizing the profits of the in-store channel.
Tracking shifts over time
With access to advanced analytics and reliable, broad-based consumer data, our new case study details how household cleaner manufacturers can better understand the relationship between these variables. It better gauges true sales growth and highlights how manufacturers can gain valuable context for their sales changes and modify their marketing and customer activation strategies to maximize incremental sales growth.
The use case outlines three essential steps to performing this highly granular analysis:
Step 1: Determine the degree of retail shifting and the destination of non-converted dollars.
Then, identify the people who shop with a retailer and the degree of retail shifting taking place. Itemizing key online and brick-and-mortar competitors provides a line of sight as to who is shopping online or at a brick-and-mortar location.
Step 2: Understand the change in buying habits over time.
In this particular case, a household cleaner brand can break down shopping trends between pre-Covid, Covid wave one, and Covid wave two to understand buying trends over the last 18 months and reveal surprising insights, including a less-than-expected in-store purchase decrease for certain items.
Step 3: Track the degree of channel leakage to ensure customer awareness.
While it’s true some shoppers prefer to shop either online or in stores, an increasing percentage of shoppers can be defined as “omnishoppers” and do both, depending on convenience and the type of household cleaner being purchased.
For example, fabric treatment solutions are mostly purchased via brick-and-mortar despite the pandemic, whereas a greater percentage of shoppers buy surface cleaning wipes exclusively online when compared with other types of surface cleaning products. Knowing if one channel is cannibalizing the other is critical to determine true incremental growth.
Household cleaner retailers that leverage omnishopper data to gain insight and context into their online and in-store sales changes can:
- Determine the demographics of shoppers
- Identify shopper behavior trends at a highly granular level (on a product-by-product basis) and channel
- Understand what percentage of their customers are omnishoppers
- Compare omnichannel performance to competitors both large and small.
Developing informed strategies to address these variables will lead to increased incremental sales—not just converted leaked customers from other channels.
Helping household cleaner brands—or any CPG manufacturer—understand the relationship between brick-and-mortar shopping behavior and who is buying what, where, and how often, is just the beginning of what an effective omnisolution can achieve.
With highly granular insights into omnishopper behavior, manufacturers in any industry can identify and understand trends faster. Once those trends are keyed in, they help inform effective strategies that speak to customers, regardless of preferred shopping channel.
Download our use case today for examples of how manufacturers can rely on verifiable and reliable consumer data to better understand their customers’ needs.