The Process Of Revenue Recovery Consists Of:

1. Identifying the precise high-risk points in the customer’s buying cycle and the customer lifecycle.
2. Implementing intelligent programs with the right content to intervene when customers reach these high-risk points. Such a point could be after a browsing session is abandoned, for example.
3. Automating those programs across multiple channels with the most relevant content for the individual customer.

This whitepaper will explain the emerging practice of revenue recovery. It reveals how retailers and ecommerce companies can boost revenue through a revenue recovery strategy informed by customer behavior. Such a strategy will nurture customer loyalty and repeat purchase activity from your most profitable customer segments.

Today’s customers are looking for a personalized approach along their entire lifecycle.

- Todd McElmurray, European ecommerce Marketing Director, Toys “R” Us

The Technology Behind Revenue Recovery

A customer intelligence tool should be able to aggregate and analyze retailers’ big data, including behavioral, transactional, lifecycle and a plethora of other indicative patterns. The difference between a simple and a sophisticated revenue recovery strategy is being able to action the real time customer data

Traditional forms of revenue recovery such as automated abandoned shopping cart emails are common practice. Additionally, many companies run dedicated re-engagement email campaigns to target customers who have become inactive. This is revenue recovery in its simplest form. However, more sophisticated revenue recovery strategies require:

• Customer intelligence tools that collect and visualize rich customer data
• Predictive analytics that anticipate points in time and behavior where strategic action would be effective
• A multi-channel automation tool that actions the campaigns driving the strategy

In short, you need a view of customer behavior across multiple channels, predictive analytics and automated, relevant marketing communications.

Promoting a business in the digital world has become highly data-driven. Marketers need to know who their customers are at every stage in the lifecycle.

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- Alex Smulders, CEO, Animal Planet Pet Food

Why There Is A Need For Revenue Recovery

Attracting new customers has long been seen as the key ecommerce business objective. In markets where there is steep growth in new customers, an acquisition-only strategy – even one demanding expensive incentives – can be very successful.

However, customers buying only once cannot be either a sustainable or profitable long-term business model. It typically costs seven times more to acquire a new customer than sell to an existing one in ecommerce, so a first-time purchase is rarely profitable.

There is an enormous necessity for revenue recovery strategies to target all types of website visitor, whether they are visiting for the first time, returning or are customer with intent to purchase.

Three quarters of customers never become profitable, and yet such heavy focus is still placed on acquisition! It’s enough to make an economist weep.”

- Ohad Hecht, Emarsys

Recent Research Substantiates This:

• 98% of website visitors never buy and of those who do, 30% buy only once
• It costs seven times more to acquire a new customer than to retain one
• Approximately $4 trillion worth of merchandise will be abandoned in online shopping carts this year
• 63% of that $4 trillion is potentially recoverable by online retailers
• Abandonment and defection behavior is increasing, and will continue to do so as more consumers shift to mobile shopping. Mobile now accounts for 10% of ecommerce website visits, but conversion rates are less than half the rate of PC visitors

The Complexity Of The Challenge

Marketers must address the issue of lost revenue in a fast-changing, competitive environment, in which:

1. The proliferation of marketing channels has added to the complexity of the buying process. Marketers often say they feel as though the customer journey is spiraling out of their control.
2. Retailers are flooded with data from a growing number of disparate sources, mostly from new technologies. They can no longer track the customer along a linear journey, often because they’re finding it hard to integrate all the data and put it to strategic use.
3. Competitive choices are increasing, as ecommerce barriers to entry are falling and new entrants with aggressive acquisition strategies lure away visitors and customers.

By adopting revenue recovery strategies supported by intelligent, innovative and integrated technology, smart retailers can thrive in this environment by:

• Extending the degree of reach and control they have over the customer journey, despite its increasing complexity
• Providing a better customer experience and more relevant offers to fend off competition

For all of these reasons, revenue recovery should be considered an urgent strategic imperative for all ecommerce companies and multichannel retailers.

Recovery Practices

There are several ways to improve the effectiveness of traditional revenue recovery practices.

Abandoned Cart Recovery

The most common revenue recovery practice is an email or ad campaign showing a customer a product that they abandoned. This is a smart and effective move. But it’s possible to optimize the performance of recovery campaigns by, for example, adding predictive recommendations. Not only are abandoned products shown, but also similar products that were bought by customers who had also browsed the abandoned item. This typically results in far higher recovery rates than standard abandoned cart campaigns, with some ecommerce businesses experiencing 67% higher click-through-rates with emails that contain such recommendations.

Reactivation Of Inactive Customers

Using historical patterns of engagement and past purchase cycles, it is possible to predict when a customer is most likely to move from an inactive to a defecting stage of the lifecycle. This allows intervention with timely automated campaigns. Designed to reactivate customers and prevent defection, these campaigns result in revenue through future purchases.

Abandoned Browse Recovery

While most visitors leave ecommerce sites without purchasing and indeed show little intent to purchase, their visit indicates they are very likely to be looking for a product that they think the site offers. With the right data, businesses can match an abandoning visitor to the right products both in the moment on-site and in follow-up campaigns, and thereby recover revenue.

Predicting And Protecting Revenue

The recovery practices mentioned above all rely on the use of customers’ past behavior to predict and influence future purchase intent and actions.

Prediction can begin far earlier in the lifecycle than when revenue is lost. Revenue recovery strategies offer the opportunity to pre-empt potential loss and protect revenue throughout the customer journey with targeted, relevant and timely communication.

By extracting information from historic and real-time customer data, marketing technology can predict visitors’ price sensitivity, category affinity, likelihood of purchase and time of purchase, and so ultimately impact revenue.

Utilizing predictive analytics, previously hidden patterns in the data help organizations generate more in-depth customer segments. The resulting segmentation is more precise and nuanced, and is ultimately based on the likelihood that a consumer will accept a given offer.

Steven J. Ramirez, Beyond the Arc

It’s Now Possible To Predict:

• Purchase patterns
• Revenue
• Customer lifetime value
• Category affinity
• Product affinity
• Developing intent to purchase
• Abandoned browses
• Device-specific engagement

Purchase Patterns

Purchase patterns that can now be predicted include: when visitors and customers will buy, what they will buy and how much they will spend. Being able to predict purchase patterns enables marketers to offer the right products instead of relying on customers and visitors to find them.

Revenue

Technology can now project revenue gain and loss based on the number of customers in a segment and their average order value. For example, across the lifecycle, how many customers are at each stage, how much they spend and when they buy. If the projected revenue from a segment is above or below projections or targets, the marketing approach can be changed accordingly.

Customer Lifetime Value

Marketers can now prioritize specific segments from which to recover revenue and choose an approach appropriate to those segments. This is because they can now predict the average lifetime values of different segments based on when and what a customer will buy. For example, they may choose to target higher lifetime value, loyal customers with their least profitable promotions, and concentrate their most profitable promotions on prospects and first-time buyers.

Category Affinity

Based on patterns of past behavior, marketing technology can detect and predict the category and product a particular customer and segment has an affinity to. Often, customers will buy from certain categories at certain stages of the customer lifecycle. Marketers can use this information to influence purchases. For example, where a category has a particular correlation with converting firsttime-buyers to active buyers, the marketer can improve results with campaigns promoting that category to that segment.

Product Affinity

By using technology that analyses additional purchases made by customers when they bought a specific product, it is now possible to offer customers the products that they are most likely to buy next through predictive recommendations. These can be shown at the cart stage, in follow-up emails and on the customer’s next visit.

Developing Intent To Purchase

Certain browsing behavior indicates more intent to purchase than others. Marketers can identify the level of intent and use predictive recommendations to reduce the number of clicks to the intended product. Such an approach reduces the opportunities for the customer to bounce. This way conversion, and therefore revenue, is protected.

Abandoned Browses

It is also possible to recognize and respond to negative engagement behavior while a customer is browsing. At this stage, it is vital to capture a customer’s email address before they leave, to enable remarketing. Technology can anticipate the perfect time to present a data capture form. By appending a history of previous interactions to that email address, such as browse behavior and category affinity, a data set of relevant products has already been created that can be utilized in future reengagement campaigns.

Device-specific Engagement

Customers carry out different tasks on different technologies. Browsing and researching products often takes place on mobile phones, while the actual purchase is done later with a PC, laptop or tablet. Therefore marketers should treat them differently when recovering or protecting revenue.

Predictive marketing allows you to project the revenue you’ll generate if you change nothing. In my experience, showing this to retailers gives them the business case, drive and direction needed to change their strategy. 

- Omer Sharon, VP Product, Emarsys

The Importance Of Multichannel Delivery In Revenue Recovery Campaigns

It is inevitable – customers will interact with your brand across multiple devices and channels. So revenue recovery campaigns must reach your customers wherever they are. Only 4% of retailers rate their online customer experience as excellent , and we have already seen how up to 24% of revenue can be lost as a direct result of poor customer experience. There is a massive gap between how the customer expects to be treated and the reality of their experiences. Implementing your revenue recovery strategy across multiple channels will lead to even greater results:

Implementing your revenue recovery strategy across multiple channels will lead to even greater results:

Email Campaigns

A second email after an abandoned cart generates a 50% increase in recovery, in contrast to the first email after an abandoned cart.

Social Ads

Reaching customers through social ads, in conjunction with email, leads to a 22% increase in the likelihood of a purchase.

SMS Messages

Conversion rates have reached 23% for retailers who use SMS messaging with a time-specific redemption offer and a strong call to action.

In-app Push Messages

54% of consumers who open a push notification convert from a targeted push campaign, compared to 15% for broadcast messages.

On-site Personalization

Personalized views on-site can increase conversion rates by 20%.

Display Ads

Website visitors who are retargeted with display ads are 70% more likely to complete their purchase.

Customer Data Integration

Most marketing technologies limit the collection of customer intelligence to after a customer has signed up. But things have moved on and new marketing technology can append a customer’s entire history to their record after registration, aggregating information from all the devices and channels they’ve used when interacting with a business. This unified customer profile enables businesses to reach more customers with personalized content informed by their behavior. As a result, revenue is more likely to be recovered and generated as the personalization is more accurate.

Channel Integration

Revenue recovery relies on the smooth integration of all marketing channels within the automation platform. This ensures that an abandoned purchase on one channel can be recuperated on the next channels the customer uses. For example, if your best customer stops visiting your website, and doesn’t engage with your emails, maybe social ads or SMS are your only chance of

Technology Integration

Retailers have fallen into the trap of patching together multiple technologies to address weak points in the customer journey. The result is disparate technologies that are seen as bugs by customers, encouraging, not preventing, abandonment. The challenge facing marketers is to have the ability to capture and collate behavioral data across multiple devices and channels. Only by having automation technologies integrated with customer intelligence is an enriched level of personalization possible.

The Importance Of Realtime Communication In Revenue Recovery

Customers abandon purchases for many reasons, but the most popular reasons fall into two categories: pricing and timing. In both cases, a well-timed response is critical. In the immediate hours following an abandoned session, where there was clear intent, the visitor is to some degree still emotionally engaged with the purchase. The trick is to reach them before that engagement tails off. If your technology is limited to, for example, one API call every 24hrs, you will have missed the boat.

There is a clear need for real-time data and automation but all revenue recovery strategies work better when the marketer has the ability to choose (and ideally, test) the right timing. If your technology is limited to one sync a day, you will fail to reach customers before they buy from a competitor, and thus fail to recover that revenue.

Weak Links Damage Marketing ROI. Eliminate Them With Revenue Recovery.

The foresight and insight that revenue recovery delivers give more control to the marketer and inform smarter marketing decisions. A successful revenue recovery strategy will deliver outstanding return on investment, making a strong case for additional investment in the customer experience.

Often it can eliminate the need for more costly compensations elsewhere; for example, reducing cart abandonment can reduce the need for discounts in recovery campaigns. Revenue recovery addresses the critical issues in ecommerce of poor conversion and a lack of repeat purchases, and arms your business for the experience-driven online shopping of the future.

To achieve all this efficiently, revenue recovery must be automated from a seamless, integrated platform. For multichannel retailers and ecommerce companies in particular, it is urgent and critical to set a revenue recovery strategy in place before your competitors do.