7 Powerful Strategies to Increase Repeat Purchase
Acquiring new customers is much more expensive than retaining an existing one. Repeat customers also bring in a significant portion of the revenue. Studies have shown that repeat customers can generate more than 40 percent of the revenue for a business, and increasing customer retention rates by 5 percent can lift profits by 25 to 95 percent.
For brands offering replenishable products, such as household goods, pet food, beauty essentials, baby products and others, which are consumed repeatedly over a period of time, it is vital to encourage customers to restock their supply on a regular basis. This kind of repeat purchase can boost revenue of investment (ROI), and ensure sustainable growth.
What Is a Repeat Purchase?
Repeat purchases are those made by an existing customer. These customers are fairly familiar with your brand, and are often driven by the need for convenience. When something has worked, why change it?
These traits make the purchase journey of repeat customers different from that of first-time buyers. In the case of e-commerce sites or apps, for example, new visitors tend to take their time browsing the pages, exploring various products, and comparing prices. Repeat customers on the other hand, already know what they want and will go straight to buy the desired product.
How to Encourage Repeat Purchases and Retain Customers
According to Alex Schultz, VP of Growth at Facebook, if 20 to 30 percent of your customers come back every month and make a purchase from you, you will do pretty well.
Also, a repeat customer is more likely to come back for more. A recent study from Shopify shows that when a customer returns for a second time, it will be 45 percent more likely for them to purchase again, and that likelihood would jump to 56 percent when they return the fourth time.
So how can you inspire your customers to make that second, third and fourth purchase? Here are seven strategies to help you increase your average repeat purchase rate.
1. Continue to engage with targeted post-purchase messaging
One mistake that many brands may have made is ceasing targeted messaging once the purchase is done. Personalized post-purchase engagement can leave your customers a positive and lasting impression, and keep your brand top of mind when they need to make a repurchase.
For example, keep customers engaged by helping them get the most out of their new purchase with useful information or relevant tips, such as a video of hair and make-up tutorials for customers who bought beauty products, or a blog post about parenting advice for someone who bought baby products.
You can use a marketing automation platform to deliver this content through email, in-app messages, push notification, and more, in real time.
2. Trigger action in real time
Customers display specific intent and behavior at different stages of the purchase journey. When it comes to purchasing replenishable items, timing is crucial. For example, a customer may restock his pet food every month, or he may replace his toothbrush every three months.
Using real-time marketing automation, you can segment your customers based on these behaviors and send relevant reminders when it is time to restock. Such automation also makes it easy to re-engage those who added items to their cart without checking out. You could then send them a trigger email with a reminder to drive conversions, but exclude those who have completed checkout in the last 24 hours.
3. Optimize transactional emails
A recent study from Experian shows that transactional emails – order, shipping updates and confirmation emails – received nearly 100 percent open rates. The conversion rates were also found to be much higher than bulk mailers.
Brands can take advantage of this type of emails and include relevant product recommendations to cross-sell. For example, an order confirmation for breakfast cereals can be a good place to recommend a popular chocolate milk to go with the cereals.
4. Increase share of wallet based on external interests
Repeat customers usually have a clear idea of what they want from you, and spend minimal time exploring other products on your site. This behavior allows you to understand what they are interested in on your site, but it does not take into account their behavior and interests on external sites. For instance, a shopper could choose you for groceries but purchase baby products from a different site. This is where AI can help by combining and analyzing first- and third-party data to uncover the customer’s interests outside of your owned channels. This way, you can be more proactive in recommending baby products to this customer when she next visits your site, and thereby increase her share of wallet.
5. Incentivize a second purchase
Discounts, promos and coupons can be effective if used correctly. For first-time buyers, these incentives are a useful way of bringing them back for a second purchase. You can also leverage AI to identify customers who haven’t purchased in a while but likely to return with incentives, and then re-engage with relevant offers to drive repeat purchases.
However, offering such perks too often could diminish revenue and create a negative impact on brand perception. So, make sure you have a solid promotional marketing strategy in place before blasting coupons out.
6. Consider loyalty programs
Another way of incentivizing repeat purchases is through loyalty programs. Discounts, early access to new products, gamified points system – these are all ways to keep customers coming back, especially for replenishable goods that customers constantly need to buy.
7. Deploy retargeting to increase conversions
Cart abandoners or customers who viewed your site without purchasing can be brought back through retargeting. The good thing about retargeting is that you can reach customers through ads even if they were viewing your website as a guest, without logging into an account. This is done through code snippets on your website which analyze their behavior and interests on your own channels as well as external sites, or through a customer list upload.
Machine learning can help you take this even further by identifying patterns in customers’ purchase histories to predict their future behavior, and see which potential customers are more likely to buy. So, you can prioritize accordingly.
In the early growth stages of your brand, it is natural for marketing to focus on customer acquisition. However, once you start securing those first customers, think of shifting your efforts gradually into encouraging repeat purchases. A good retention strategy powered by AI and data can help you keep your customers coming back and continuously generate repeat sales.
* Want to learn more about how you can use an AI-based marketing automation platform to improve customer engagement and drive repeat purchase? Get in touch with our team today for an exclusive consultation.
WE ARE HERE TO HELP
YOU MIGHT ALSO LIKE
As COVID-19 restrictions begin to lift, food and beverage (F&B) services such as restaurants and bars around the world are starting to reopen their doors. While different markets have different time schedules, the social distancing rules being enforced by governments are similar, such as maximum capacity limits, keeping tables 1.5 meters apart and checking temperatures on arrival. Some of the consumer behaviors that have shifted since the beginning of the pandemic are likely to stay in this new, socially-distanced normal. While people are beginning to venture out to dine, takeaway and delivery numbers are still up as people remain wary and increasingly prefer to cook and eat at home. According to a study done by Hunter, a food and beverage marketing and PR firm, 54 percent of Americans are cooking more than they were before the pandemic. In the UK, an earlier poll showed that 60 percent of 18 to 24 year olds surveyed had already increased the frequency of using food delivery services, while 40 percent of 35 to 54 year olds saying they would do so. At the same time, customers have also displayed an increased interest in food hygiene, healthier, immune-boosting options, and locally-sourced products. To survive
Demand for e-learning has grown significantly over the past decade as people and companies increasingly look to upskill online. According to Business Wire, the global corporate e-learning market is expected to be worth US$49.87 billion by 2026. The US and Europe make up over 70 percent of this, while Asia Pacific is the fastest-growing region, with an anticipated growth rate of 20 percent a year. Some of the big players in the market include Udemy, SkillShare, and Coursera. Despite the positive prospect, what do e-learning providers need to do to play the long game in this thriving market? The answer lies in smart strategy and advanced technology like artificial intelligence (AI) and deep learning. The Rise of E-Learning This growth in the e-learning market is being driven by several factors: A glut of new e-learning technology, the need for talent enhancement and retention, and a desire for more convenient and cost-efficient ways to learn. The COVID-19 pandemic has only accelerated this growth by pushing people to spend more time online. However, competition in the e-learning industry is increasingly fierce, and there are still several challenges providers need to overcome. The mental hurdle is one. E-learning is still a relatively
Marketing has always been highly dependent on data. And in today’s rapidly moving world, the importance of managing vast quantities of diverse data from disparate sources is growing. “There are three main issues when it comes to data management for marketers,” explains Dr Min Sun, Chief AI Scientist at Appier. “The first is data quality – the maxim of ‘garbage in, garbage out’ is critical for marketers. Once data quality is assured, the second factor to consider is the usefulness of the data. What data is valuable and which data sets can be used together? Finally, companies need to ensure they have robust governance in place. These cover the legal and corporate obligations including jurisdictional frameworks, such as General Data Protection Regulation (GDPR) in Europe, the Personal Data Protection Act (PDPA) in Singapore and others.” What Is ‘Good’ Data? There are several dimensions to data quality. Dr Sun says that issues such as consistent errors and inconsistent noise in data can significantly decrease the usefulness and value of even huge data sets. However, a more subtle issue can come even when the data is completely correct, but the assumptions underlying the selection criteria are biased or skewed. As a