Shoppers turn to Twitter as a source of information, recommendations, and deals in the buying process.
From ordering home goods to splurging on spring fashion, shopping is a favourite pastime of Twitter users. To help retailers understand how people navigate the purchase process and what drives them to buy, we recently conducted studies with Millward Brown* and Crimson Hexagon**. The insights we gained can help you maximise sales by sending Twitter shoppers the right message at the right moment.
Twitter users are big retail shoppers.
Twitter users’ shopping habits make them a valuable audience for retailers. According to a Millward Brown survey of women on Twitter who had recently purchased household staples, Twitter users have bigger budgets and buy more often than non-users.
Users in our study reported they planned to spend 21.7% more than non-users over the next six months and said they had made nearly twice as many purchases in the past month. And many of these purchases were made online—on average, Twitter users shopped online 6.9 times a month, while non-users shopped online just 4.3 times a month.
Shoppers make use of Twitter throughout the purchase cycle.
Whether they’re learning about a new product or on the brink of buying, shoppers rely on Twitter for information and advice. Our survey with Millward Brown showed that nearly half (49%) of female Twitter shoppers say Twitter content has influenced their purchase decisions, which makes the platform prime real estate for brands.
These shoppers on Twitter are also engaged: They’re 160% more likely to stay up-to-date on brand news and promotions, 120% more likely to search for deals and sales, and 240% more likely to converse with a brand than retail shoppers on the average social network.
Shoppers use Twitter differently for different retail categories.
As marketers know, shoppers hunting for home improvement products navigate the purchase process differently than those in the market for consumer electronics. Understanding these differences can enable retailers to fine-tune their marketing messaging. We partnered with Crimson Hexagon to delineate them.
We found that while users turn to Twitter at every stage of purchase for every retail category, the share of conversation for each stage can vary. For instance, 51% of apparel-related Twitter retail conversations indicated users were in the “awareness” phase—but this was true for just 8% of grocery/pharmacy conversations.
Twitter conversation reveals what drives retail shoppers to buy.
After analysing share of conversation at each stage of the purchase process for each retail category, we took a closer look at the content of these conversations to learn what ultimately motivates retail shoppers to buy.
We found that purchase motivation varies by retail category as well. For example, when in the purchase intent mind-set, consumer electronics shoppers talked most about advertisements; apparel shoppers Tweeted most about price; and grocery/pharmacy shoppers buzzed most about recommendations.
To help you apply this data to your marketing strategy, we’ve identified the “purchase funnel hot spot” and “top sales driver” for each retail category. The “hot spot” is the area of the purchase funnel where a high proportion of Twitter conversation happens relative to other retail categories. For example, 25% of the Twitter conversation around big box retail was related to brand or product evaluation—this was higher than for any other retail category. The “top sales driver” tells you what is driving the most purchase-related conversation in each category. For big box, this was customer service. These insights reveal areas of opportunity for brands in each retail category to help deliver consumers the right content at the right time.
Big box retail
Purchase funnel hot spot: Evaluation
Top sales driver: Customer service
Recommendation: To maintain or grow your market share, make sure your customer support is competitive. In this Tweet, @WalmartToday links to a heart-warming story about an employee who goes above and beyond for her customers.
Purchase funnel hot spot: Post-purchase chatter
Top sales driver: Advertisements
Recommendation: Create incentives for people to Tweet about their purchases and release buzzworthy advertisements. Here, @hhgregg Tweeted a Gallery Card of four Valentine’s Day e-cards featuring their products. Users who Retweeted one of the images earned a chance to win a $100 gift card.
Purchase funnel hot spot: Purchase intent
Top sales driver: Price
Recommendation: Use engaging Promoted Tweets with images to promote deals and sales and drive traffic to your online store. In this instance, @Gap encourages users to visit its website by offering them a 40% discount.
Purchase funnel hot spot: Conversion
Top sales driver: Seeking suggestions
Recommendation: Use visually engaging Tweet formats to distribute branded home improvement how-tos, and include links to product pages where users can easily convert to purchase within a click or two. Here, @HomeDepot uses an image to alert its audience to a new trend, and directs them to a page where they can buy the materials necessary to pull it off.
Purchase funnel hot spot: Interest/consideration
Top sales driver: Recommendations
Recommendation: Share product recommendations that align with trends and meet the needs of your customers. Knowing that many people would be interested in having a special dinner on Valentine’s Day, @Safeway used this Tweet to share an idea for a romantic meal.
*Millward Brown study
In June and July of 2014, we commissioned Millward Brown to use a 10-minute online questionnaire to survey 1,128 US women age 21-54 who said they had purchased a household cleaning product or an item from a home goods store in the past year. Millward Brown compared Twitter users to the average user of six top social media networks (Twitter, Instagram, Facebook, Pinterest, Vine and Tumblr). A user of any social network was defined as someone who logged in at least once a month.
**Crimson Hexagon study
We partnered with Crimson Hexagon to analyse US retail chatter on Twitter from February 2013 to January 2014. We first divided retail chatter on Twitter into five categories, such as “consumer electronics” and “big box retail”. Next, we used keyword analysis to determine the share of conversation for each stage of the purchase process for each category. (For example, a Tweet containing a product name such as “shirt” and a phrase indicating consideration such as “I need” would have been added to the “consideration” bucket for the “apparel” category.) Next, we looked at how many Tweets in each category included purchase driver keywords paired with purchase intent keywords on Twitter from September 2011 to January 2014 (e.g., a Tweet with the keywords “I want to buy”, “computer”," and “customer service” would have been bucketed under the “customer service” purchase driver for the “consumer electronics” category.)