Automated Retention Marketing Enter ecommerce s new best friend. Retention Science offers a platform that leverages big data and machine learning algorithms to maximize customer lifetime value. We automatically aggregate sales and transaction data, we collect behavioral data on site, and we publicly crawl 3 rd party data to create the best possible picture for every individual customer. Our engine will profile each customer based on all this information and generate predictions for the best campaign to get each customer to convert. Our customer profiling engine will improve purchase rate and make sure first time buyers come back to your business by sending relevant offers to customers at the optimal time. Customer Lifecycle Your customer s relationship with your brand or company will follow a cyclic pattern of activity, called Customer Lifecycle. This cycle starts with customer acquisition, periods of engagement followed by lapses in activity, and ends with the inevitable churn. The following paragraphs describe these stages and their respective effects on the company. Acquiring new customers is 6x- 7x more expensive than retaining existing customers Before earning a customer s business, you must first acquire him or her. Some customers come to you on their own; these organic customers are the most sought after type of customers due to extremely low acquisition cost. Unfortunately, such customers are rare. Because of that, most companies need to invest extensively in acquisition marketing, characterized by heavy advertising and heftier incentives. The results of such campaigns are customers of dubious
quality that are more likely than not to come to your site, leave, and never come back. Acquiring new customers is a lot more expensive than retaining existing ones. In fact, according to a report by Bain & Company, it costs 6-7 times more to acquire a new customer than retain an existing one. After a customer is acquired, the next step is to activate them. Activating a customer means enticing him to perform his first transaction, whether it is subscribing to a service or buying an item. Some customers are activated immediately; others vanish without making a single purchase. Generally speaking, the sooner the customer is activated, the better the odds are of him being a repeat customer, which is the type of customer every business wants. However, it is not always the case, especially when it comes to customers that came to your site through heavy discount advertising. Even though such customers may get activated right after being acquired, many of them will have already made up their minds to never come back to your site. It will then be up to your loyal customers to carry the burden of paying for such discount scavengers. Until very recently, the predominant managerial school of thought was to concentrate on winning the largest number of customers during the acquisition stage, no matter the costs. Such approach is no longer practical in modern world of widespread Internet access, where a quick search will tell your customer which of your competitors is offering cheaper products he is interested in. The only way a customer will continue using your store is if he is loyal to your company. Such attitude cannot be acquired. It must be cultivated - cultivated by understanding and attending to individual customer s needs and nurturing and growing the relationship. During this loyalty cultivation stage, customers will go through periods where their level of engagement decreases. Having invested in getting to know your customer, it will be easier to understand the reasons behind such lapses in activity and take appropriate actions to bring the customer back. In a study done by Rockefeller Corporation, 68% of customers left because they thought the company did not care about them. But by continuing to meet or exceed customers ever- changing expectations there should be no reason for them to stop doing business with your company. Therefore, strategically minded companies are encouraged to concentrate their marketing efforts on retaining customers by developing a lasting relationship. There is another built- in benefit of focusing on prolonging customer development stage. Besides the fact that their profitability tends to increase over the life of retained customer just by making more purchases, loyal customers are one of the highest drivers of organic traffic to your site (Emmet Murphy & Mark Murhpy). It is not uncommon for them to encourage their friends to visit your site or subscribe to your service. In fact, satisfied customers tell on average 9 people about a positive interaction they had with a company
(allbusiness.com). This free organic advertising can help reduce the amount of resources spent on customer acquisition while increasing the share of customers that are more likely to become loyal repeat buyers. Although more and more progress is being done towards improving business- to- customer dialogue with the advent of Big Data and new algorithms, such customer- centric approach is still hard to implement, which is why many customers (most, in fact) end up leaving the company sooner or later. This stage of customer lifecycle is called churn and is described in the next section. Customer Churn On average, a company loses between 10%- 30% of its customers every year (McKinsey). This percentage is even greater for smaller businesses where the amplitude of customer in- and out- flux is larger due to smaller numbers of customers. A customer is considered to have churned when he is no longer uses company s service(s). With subscription- type business models, detecting churn is relatively straightforward. Usually, when a customer stops paying for his subscription, they have churned. It is worth noting here that the same customer can later re- subscribe; in this situation his lifecycle would start from beginning. There are several reasons for this: first, the chances of a customer returning after unsubscribing are generally small and second, when a customer unsubscribes, he is making a conscious effort to terminate his affiliation with the company. Know when to re- activate your customers before you lose them! Defining churn for e- commerce businesses is more challenging, mainly due to the fact that even the most active customers only have a few transactions a year with long, sometimes lasting months, periods of inactivity in between. For instance, even the most loyal customer is unlikely to purchase more than three or four pairs of shoes from a site that specialized in online footwear retail just because it is hard to go through more than several pairs of shoes in a year. At the same time, going more than a year without a single purchase is not uncommon for a customer who shops for seasonal apparel from a hiking/mountaineering store. In extreme cases, we saw customers return to purchasing after a +20 month lapse. Most companies set a somewhat arbitrary time limit on user s inactivity after which the user is considered churned. While this approach is better than nothing, it is far from perfect. The deficiency of this method comes from the fact that it is close to impossible to determine the exact moment when a customer makes the decision to leave. Sometimes, this decision comes even before the first purchase. Other times, the customer buys again after the churn period due to his seasonal preferences. Identifying a churned customer in a timely fashion is one of the most important and challenging tasks of business intelligence. It is inefficient to spend as much
on churned customers as it is on active ones to try to make them to purchase again. Being able to precisely pinpoint when customers churn can help shed light on the reasons for these events, and, most importantly, take immediate actions that could prevent customers from churning. Even a 5% increase in customer retention due to decreased customer churn increased profits by up to 125% in a study done by Bain & Company. This brings us to the next topic of the paper: customizable personal incentives. Personalized Incentives Every customer is different. Every customer has different reasons for buying (or not buying) something from your store, subscribing to your site, browse your resource, or deciding to stop using your service. Because of that, it is imperative to get to know each customer as well as possible in order to detect and react to his constantly changing behavior, especially when that behavior is associated with inactivity. To bring back customers business, marketing managers utilize various incentives. These incentives include discounts, free shipping, loyalty points, and others. With the advent of the email marketing in the last two decades, it became increasingly easier and cheaper to target customers with various offers. Indeed, it became so easy to reach out to customers with these incentives that many of us are getting a barrage of emails every day with coupons, discounts, and promotions. While some may argue that sending thousands or even millions such emails every day costs close to nothing nowadays, the outcomes of such campaigns are rarely optimal. As an example, consider an online e- commerce store that sends out a generic 20% discount offer to all of its customers. On any given day, even without any incentives, most of these customers are not going to buy anything no matter what incentives they receive. A much smaller portion of customers will buy something that day are going to make a purchase no matter what incentives they receive. Finally, there is another segment of swing customers that would be converted to make a purchase with the right incentive. However, that incentive can be a 5% discount, a fixed amount off, or a free shipping coupon. Thus, what happens when everyone receives that 20% discount offer is the following. Customers that would have bought something anyways are given a discount (that is, a 20% revenue loss), customers that would have been converted with a smaller discount do the same. Customers that are indifferent to percentage discounts that day do not buy anything, which is a huge foregone
opportunity. Even for customers that converted at 20%, a portion of those will not purchase again unless offered a sizeable discount, reducing company s profit margin. Yet this generic offer will ignore a customer who, given a 30% discount, will become a loyal customer that will more than cover this discount with future purchases. Finally, some percentage of customers unsubscribe from the store s mailing list completely due to continuous influx of irrelevant emails, thereby severing the most important, if not the only channel for business- to- customer communication. Angering customers in such way is a bad idea: A dissatisfied customer will tell between 9-15 people about their bad experience, while more than 10% will tell more than 20 people, according to a report from White House Office of Consumer Affairs. One- size- fits all marketing doesn t work. Individually tailored campaigns do! Start sending the right offers, to the right customers, at the right time. This example aims to warn managers against generic marketing campaigns. To combat this method s inefficiency, one must learn customers preferences. While it can be difficult to collect such data, many preferences can be inferred from observing customer behavior on site and combing these observations with the analyses of their past transactional data. For instance, a manager could track customer s actions from the moment an offer email is sent out. By keeping track of what offer that customer received and his resulting actions, it is possible, over time, to build a profile on that customer with his preferred type of incentive. Also, it is possible to determine the optimal timing of when to send out the offer. Some customers prefer to check their emails in the mornings; others are more responsive after the workday. Some are interested in checking out daily deals, others seem to want to limit the amount of emails they get every day. Finally, by tracking customer s actions online, it is possible to identify the products he is interested in and, utilizing his preference profile, give him the right incentive at the right time to induce a transaction. Customer retention is a challenging, undervalued and oftentimes ignored aspect of business models. And even though the paradigm seems to be slowly shifting from focusing on customer acquisition to more intelligent and efficient customer retention, not every company, especially young e- commerce businesses, has the necessary resources or desire to allocate those resources to optimizing its retention marketing program. Yet such an investment is a worthwhile one. Observations show that most of revenue in a given time period comes from the newly acquired customers. The absolute vast majority of those customers will end up never purchasing again. In our study done with four small to medium online retailers, almost 90% of customers were one- time buyers. But if a company manages to entice a small fraction of its existing users to make a repeat purchase (a fraction comparable to the number of newly acquired users during that time frame), then the revenue for that period will double! This two- fold increase will come at a significantly lower cost due to much lower costs of retaining customers. And this back- of- the- envelope calculation does not even
include future revenue from repeat customers, which are a lot more likely to purchase again than the customers that only made one purchase. Key Takeaways Your business should address the importance and benefits of investing in improving and optimizing customer retention: Customer Lifecycle, resources are better spent on prolonging the active part of the cycle rather than on acquiring new customers or trying to bring back churned ones. Customer Churn, businesses must actively identify and predict churn indicators to potentially prevent the churning point of a customer. Data as a tool, combining online activity with the existing transactional data can help businesses personalize customers shopping experience with personal incentives and individualized product recommendations delivered at times and frequencies tailored to each customer. Do not waste your company s resources. Does not agitate the customer with senseless offers. Optimize your revenue streams, improve customer experience, and, most importantly, strengthens the loyalty bond between your business and your customer. While easy conceptually, such customer- centric approach to retention in practice requires enormous amounts of carefully collected data, incisive and relevant mathematical models, and sophisticated machine- learning algorithms. REQUEST A DEMO! 310.598.6658 or sales@retentionscience.com