Finally on an upswing, the furniture industry has been slowly acclimatising to the new trends it faces. Among them is the challenge of online marketing and data exploitation. Anders Ekman explains why retailers should take notice of terms such as Big Data, Data-as-a-Service and Real-Time Data …
It’s no secret that Big Data can provide a myriad of competitive advantages, but there are still some lesser-known applications for Big Data solutions that can specifically benefit companies in the furniture industry.
The days of marketing strategies based solely on newspaper and television ads are now a thing of the past. Industry leaders are finding that claiming a stake in the digital marketplace is no longer an option, but a necessity to keep up with the competition. With this uncharted territory comes bigger opportunities than ever before to tap into the troves of data that in-market consumers are unknowingly leaving behind.
A study by Franklin Furniture Institute found that 51% of respondents research furniture online prior to purchasing, and every click leaves behind a virtual trail of crumbs leading straight to consumers, where a purchase is imminent. If furniture retailers learn how to follow the trail they can reap unending benefits.
Tapping into Fast Data
Data-as-a-Service (DaaS) is the facilitator of data-driven marketing strategies. The term DaaS comprises the processes of gathering and leveraging various types of Big Data resources to ultimately improve a business’ revenue.
There are three main types of data that can be leveraged by DaaS: Foundational Data – internal data combined with additional demographic and firmographic enhancement and Hard-to-Find-Data; Onboarded Data – offline data transformed into addressable online identities; and Fast Data – real-time behavioural data.
The most successful data-driven marketing plan integrates all three data sets into a comprehensive database to effectively segment and target prospects – but for a furniture company looking to test the waters of data-driven marketing, tapping into the Fast Data resources is a good place to start.
“Fast Data is an invaluable asset to the furniture industry as it aggregates event- and behavioural-driven data to determine purchase intent as it occurs”
Fast Data is an invaluable asset to the furniture industry as it aggregates event- and behavioural-driven data to determine purchase intent as it occurs. Retailers who tap into this resource enjoy an almost unfair competitive advantage in having exclusive knowledge about who is actively searching for specific categories of furniture that they, or their competitor, sell.
The retailer now has the first opportunity to reach out to the consumer who has inadvertently already shown interest in making a purchase. As opposed to casting a wide net in a newspaper or television ad and hoping to catch the eye of an interested consumer, the retailer is now focusing marketing spend on an already-warm lead that just needs some encouragement and reminders of their interest in purchasing.
Types of Fast Data
There are three main types of Fast Data that marketers can employ for their targeted marketing. Most Fast Data-driven marketing strategies utilise a combination of all three categories, as they will often overlap in one way or another.
The first type is social purchase signaling, or signals derived solely from social media outlets. DaaS solutions scour the internet in search of qualifying phrases posted to social sites that are proven to imply imminent purchase in certain products – for example, ‘excited about the move’ or ‘shopping for a new couch today’.
Such signals signify the opportune moment to market to consumers who are already primed for purchase and open to accepting a product offer – so it might as well be yours.
Second is discretionary purchase signalling, or leveraging signals which imply an influx of discretionary income. Consumers who find themselves with a suddenly higher allocation of discretionary income are more apt to make a purchase which they previously considered a luxury – such as a new bedroom set or sectional sofa. These signals include customers who have secured new credit sources or have recently been promoted or transferred to a better-paying occupation.
The third category of Fast Data is life event signalling – being aware of big changes that are generally followed by certain purchases. For example, baby shower registries or web searches on being a first-time parent signal the impending purchase of nursery furniture. Weddings also have a similar pattern with registries and search behaviour.
New movers are the most substantial resource of life event signals as they represent a gold mine of opportunity for retailers. In the US, new homeowners spend more within the first six months than the average consumer spends in three years. DaaS solutions access current, real-time databases of new movers and provide this information to retailers for targeted outreach.
But won’t they find it odd?
A concern of many retailers is whether or not poignant strategies based on mined information will turn consumers off their brand. The good news is consumers are becoming more accustomed to their information being used to construct personalised outreach, and now generally expect it.
A recent study by Yahoo and IG shows that 55% of consumers are more likely to engage in a personalised ad versus a general one. A study by Accenture showed that 68% of Millennials react more positively to that approach too.
Although implementing Big Data can be overwhelming at first, investing in Data-as-a-Service can provide an unparalleled competitive advantage for retailers looking for a more finely-tuned customer acquisition strategy. In a crowded marketplace, it could be your ticket to unprecedented success.
Anders Ekman is the president of DataMentors, a provider of Data-as-a-Service marketing solutions based in Florida. This article was featured in the October issue of Furniture News magazine.
