BUSI 442 Week 5 Customer Retention Strategy Project Phase 1 Example

Retention Strategy Project, Phase 1: Customer Analysis, Lead Generation and Retention Diagnosis

Introduction and Purpose

Northfield Garden Supply sells seeds, plants, soil and tools online to home gardeners and wholesale to landscaping companies. Like many seasonal retailers, it spends heavily each spring to attract new customers, many of whom buy once and never return. The owners have asked for a customer retention strategy. Roberts and Zahay (2018) treat retention marketing as a set of activities that keep customers buying and growing in value, built on data about each customer and on the lead generation and optimization practices that bring the right customers in. This project develops that strategy in two phases. Phase 1, presented here, analyzes Northfield's customer base, examines how it generates and converts leads, diagnoses why customers leave and sets objectives. Phase 2 will design and justify the retention program.

Company Situation

Northfield was founded as a mail-order seed company and moved online fifteen years ago. It now offers about 2,400 products, ships from one warehouse and employs 46 people. The company's figures for the most recent year appear below.

Two numbers stand out. Northfield acquires 26,000 customers a year at $38 each, nearly $1 million in acquisition spending, yet only about one in five of them comes back the following season. Each spring, the company largely replaces the customers it acquired the year before.

Competitive Context

Northfield competes with three kinds of rivals. Home improvement chains sell seeds and common plants cheaply and conveniently, especially for customers who want to buy in person on a spring weekend. Large online seed companies offer broad catalogs and strong brands. Local nurseries offer advice and the chance to see plants before buying. Northfield cannot match the chains on convenience or the large seed companies on breadth. Its advantages are a curated selection suited to its region, plants shipped at the right planting time and a staff horticulturist who answers customer questions. Those advantages matter most to customers who want to succeed, which is why a retention strategy built on helping customers grow well fits the company's position better than one built on discounts, where the chains will always win.

Customer Base Analysis

Segmenting by Recency, Frequency and Monetary Value

The analysis scored every customer who bought in the past three years on recency, frequency and monetary value. Fader et al. (2005) demonstrated that recency, frequency and spending can be tied to customer lifetime value, so these scores are not only a way to sort the list but a basis for forecasting each customer's future purchases. The resulting segments are summarized below.

The pattern is typical of retail: fewer than one customer in ten produces two fifths of revenue. The largest group, one-season buyers, produces little revenue, but it represents the company's biggest opportunity, since some of these customers resemble the devoted gardeners at the start of their relationships.

Estimating Customer Value

The analysis estimated lifetime value for each segment using margin, purchase frequency and retention. A devoted gardener contributes about $185 in gross margin a year and stays for many seasons, producing an estimated lifetime value of about $640. A one-season buyer contributes about $28 and rarely returns, so after acquisition cost the relationship loses money.

Reinartz and Kumar (2000) warn that long-life customers are not automatically the most profitable, and the analysis confirms that some lapsed regulars bought small amounts for many years. Value, not tenure, should guide where the strategy invests.

Seasonality of Value

Customer value at Northfield is concentrated in a few months. About 70 percent of retail revenue arrives between February and May, with a smaller peak for fall bulbs in September and October. A customer's decision to return is therefore made, in effect, once a year, usually in late winter, when gardeners plan and order seeds. A retention strategy must be present at that moment. Contact in midsummer matters only insofar as it keeps the relationship alive until the next decision point, while contact in January and February decides whether the customer comes back. This calendar shapes both the diagnosis below and the program in Phase 2.

Why Retention Matters to the Company's Value

Gupta et al. (2004) developed a method for valuing a firm's customers and applied it to several companies, finding that a 1 percent improvement in retention raised customer value, and with it firm value, by roughly 5 percent, far more than a 1 percent improvement in margin or in acquisition cost. Rust et al. (2004) proposed a customer equity framework in which the total discounted lifetime values of a firm's customers serve as a guide to marketing strategy, with value equity, brand equity and relationship equity as the drivers that marketing can improve.

Both studies point Northfield in the same direction. Lifting the share of first-season buyers who come back from 22 to 30 percent would add thousands of returning customers each year without additional acquisition spending, and the effect would compound as those customers continue in later seasons. Retention is not a secondary goal for the company; it is the most powerful lever on its value.

The Drivers of Customer Equity at Northfield

The customer equity framework suggests examining three drivers. Value equity, customers' judgment of quality, price and convenience, is mixed: survey respondents rated Northfield's plant quality highly but its shipping costs poorly. Brand equity, customers' subjective view of the company, is strong among devoted gardeners, who describe Northfield as knowledgeable, and weak among one-season buyers, many of whom could not recall the company's name when surveyed. Relationship equity, the ties that keep customers returning beyond their judgments of value and brand, is almost absent, since the company offers no rewards, no recognition and little personal contact after the first order. The analysis therefore suggests that relationship equity is where Northfield has the most room to improve, while value equity needs targeted attention to shipping costs.

Lead Generation

Where Leads Come From

Northfield's leads, prospective customers who have shown interest but not yet bought, come from five sources: organic search for plant and seed names, paid search during spring, social media posts showing gardens and harvests, a free online garden planner that requires an email address, and referrals from existing customers, who currently receive no reward for referring. The planner is the company's most productive lead source: about 14,000 people a year create plans, and 31 percent of them buy within the season, against 9 percent of other email subscribers.

The Value of Referred Customers

Referrals deserve more attention than Northfield gives them. Schmitt et al. (2011) examined a bank's referral scheme and reported that customers brought in by friends earned more margin and were more likely to stay than other customers, making them more valuable over time even after the cost of the referral reward. Kumar et al. (2010) demonstrated that customers vary in the value of the referrals they generate, that this referral value differs from the value of their own purchases, and that firms can identify and encourage the customers most likely to make profitable referrals.

For Northfield, the implication is that a referral program should be part of the retention strategy, not just an acquisition tactic. Referred gardeners arrive with a relationship already in place, and devoted gardeners, who talk about their gardens with neighbors and friends, are likely to be strong referrers.

Wholesale Accounts as a Retention Segment

Northfield's 300 landscaping accounts behave differently from retail customers. They buy throughout the growing season, place larger orders and stay longer, with about 81 percent active from one year to the next. Their reasons for leaving are practical: shortages during the peak, late deliveries and pricing. Although the retention strategy focuses on retail customers, where the losses are largest, Phase 2 will include a short section on wholesale accounts, since keeping a single landscaper is worth as much as keeping dozens of retail gardeners.

Acquisition Quality

Not all new customers are equally likely to stay, and the source of a customer predicts much of the difference. When the analysis followed last year's new customers into this year, planner users returned at 34 percent, referred customers at 37 percent, organic search customers at 23 percent and customers acquired through spring discount ads at only 12 percent. The discount ads brought in many customers cheaply, but most came for the price and left when it ended. This finding connects acquisition to retention: shifting part of the acquisition budget from discount ads toward the planner, content and referrals would bring in customers who are more likely to return, which eases the retention program's work before it starts.

Lead-to-Customer Optimization

Leads become customers through a series of steps that can each be improved. The analysis traced the path from lead to first order for planner users and email subscribers.

Several weaknesses appear. The welcome series for general subscribers consists of a single discount email, which many never open. Planner users receive no messages connected to their plans, so the company misses a natural chance to recommend the plants they have chosen. Product pages offer little growing advice for beginners, who make up most new leads. Phase 2 will propose and test changes at each step, such as a welcome series built from each lead's interests and planner-based recommendations.

Testing the Path

Each weakness in the lead path can be tested. The welcome series for general subscribers can be compared with a three-message series that asks about each subscriber's garden and recommends products to match. Planner users can be split between the current silence and a sequence that turns their plans into a shopping list at planting time. Product pages for beginner favorites can gain short growing guides, compared with the current pages on conversion and, later, on return rates. Judging these tests on second-season returns as well as first orders keeps optimization aligned with retention.

Retention Diagnosis: Why First-Season Customers Leave

The analysis used three sources of evidence: a survey of 1,200 one-season buyers, the company's complaint records and email engagement data.

The survey found that the most common reason for not returning was a disappointing first season: 38 percent said that some of their plants or seeds failed, and most of them blamed themselves or the products rather than conditions they could not control. Another 24 percent said they simply forgot about Northfield by the next spring, and 17 percent said they bought from a local store instead. Complaint records showed that first-order problems, especially plants damaged in shipping, were followed by very low return rates. Email data showed that most one-season buyers stopped opening emails by midsummer, when Northfield's messages were still promoting spring products.

Bolton (1998) linked accumulated satisfaction to the length of relationships and showed that recent customers react more strongly to new experiences, which helps explain the pattern. A first-time gardener whose tomatoes failed has no years of good experiences to balance that disappointment. The diagnosis suggests that Northfield loses customers less because of competition than because of failure, forgetfulness and irrelevant contact.

What Different Segments Need

The survey also showed that the segments leave for different reasons. Promising newcomers, who placed larger first orders, most often cited plant failures and said they would have welcomed advice. One-season buyers with small orders most often said they forgot about Northfield or bought locally, suggesting that timely reminders could bring some of them back. Lapsed regulars gave the most varied answers, including moves, health and changes in available time, along with a few who were unhappy with price increases. Devoted gardeners reported high satisfaction but said that they would like recognition, such as early access to new varieties. A single retention message sent to all segments would fit none of them well.

Predicting and Targeting Defection

A retention strategy needs a way to identify which customers to approach. Neslin et al. (2006) compared many churn prediction models submitted by researchers and practitioners and found that predictive accuracy varied substantially across approaches, and that more accurate models could produce meaningful financial gains for retention programs. Northfield can build a simple model from its own data, drawing on signals such as a troubled first order, whether the customer used the planner, how often emails are opened and which categories were bought, to estimate each customer's chance of not returning.

Prediction is not the whole answer, however. Ascarza (2018) ran retention campaigns as field experiments and found that aiming them at the riskiest customers often wasted effort, because those customers were frequently not the ones a campaign could persuade. Better results came from targeting customers whose likelihood of staying was most sensitive to the intervention. Northfield should therefore test its retention messages on random groups across risk levels and direct them to the customers who respond, not simply to those predicted to leave.

Data and Systems Readiness

The analysis also revealed gaps in Northfield's data that Phase 2 must address. Customer records from guest checkouts are not linked to email subscribers, so the company cannot always tell whether a subscriber has bought. Planner data are stored separately from orders. Complaint records are kept in the customer service inbox rather than in the customer database, which is why first-order problems were not visible to marketing until this project matched them by hand. Before the retention program can target customers well, the company needs a single customer record that combines orders, email engagement, planner use and service contacts, updated at least daily during the spring season. These steps are modest in cost for a business of Northfield's size and are the precondition for everything else.

A Biblical Perspective on Retention

The diagnosis showed that many customers leave because their gardens failed and they lost heart. Paul urged the churches of Galatia to keep doing good without losing heart, promising a harvest at the proper time to those who persevere (English Standard Version Bible, 2001/2016, Galatians 6:9). The verse speaks of perseverance in doing good, and it fits a retention strategy built on helping customers succeed. A business that walks alongside a discouraged first-time gardener, explaining what went wrong and how to try again, serves that customer's good, and the relationship that follows rests on care rather than on discounts.

Objectives for Phase 2

Each objective follows from the analysis: the return rate addresses the central problem, reactivation targets lapsed regulars, planner conversion improves lead optimization, referrals bring customers who are more likely to stay, and a lower unsubscribe rate protects the channel that retention depends on.

Implications for Phase 2

The analysis points toward a program with five parts, which Phase 2 will develop in detail. First, a first-season success program that helps new customers grow what they bought, through planting guides, timely care emails and quick resolution of problems. Second, a late-winter campaign that reaches customers while they plan the coming season, built from each customer's past purchases. Third, a referral program aimed at devoted gardeners and promising newcomers. Fourth, a reactivation series for lapsed regulars. Fifth, optimization of the lead-to-customer path through a welcome series and planner-based recommendations. Every part will be tested against a holdout group, guided by the churn model and judged by the objectives set above.

Conclusion

Northfield Garden Supply's growth is limited less by its ability to find customers than by its ability to keep them. The customer base analysis shows a small group of devoted gardeners producing most of the value and a large group of one-season buyers who cost more to acquire than they return. Research on customer value shows that retention is the strongest lever on the company's worth, and research on referrals and churn points to practical tools. The diagnosis identifies the main causes of defection: failed first seasons, forgetfulness and messages that do not fit the customer. Phase 2 will design a retention program around those causes. It will also set a budget, assign responsibilities and describe how each program will be tested, so that by the end of the next season the owners will know which efforts brought customers back and which did not.

References

Ascarza, E. (2018). Retention futility: Targeting high-risk customers might be ineffective. Journal of Marketing Research, 55(1), 80-98. https://doi.org/10.1509/jmr.16.0163

Bolton, R. N. (1998). A dynamic model of the duration of the customer's relationship with a continuous service provider: The role of satisfaction. Marketing Science, 17(1), 45-65. https://doi.org/10.1287/mksc.17.1.45

English Standard Version Bible. (2016). Crossway. (Original work published 2001)

Fader, P. S., Hardie, B. G. S., & Lee, K. L. (2005). RFM and CLV: Using iso-value curves for customer base analysis. Journal of Marketing Research, 42(4), 415-430. https://doi.org/10.1509/jmkr.2005.42.4.415

Gupta, S., Lehmann, D. R., & Stuart, J. A. (2004). Valuing customers. Journal of Marketing Research, 41(1), 7-18. https://doi.org/10.1509/jmkr.41.1.7.25084

Kumar, V., Petersen, J. A., & Leone, R. P. (2010). Driving profitability by encouraging customer referrals: Who, when, and how. Journal of Marketing, 74(5), 1-17. https://doi.org/10.1509/jmkg.74.5.001

Neslin, S. A., Gupta, S., Kamakura, W., Lu, J., & Mason, C. H. (2006). Defection detection: Measuring and understanding the predictive accuracy of customer churn models. Journal of Marketing Research, 43(2), 204-211. https://doi.org/10.1509/jmkr.43.2.204

Reinartz, W. J., & Kumar, V. (2000). On the profitability of long-life customers in a noncontractual setting: An empirical investigation and implications for marketing. Journal of Marketing, 64(4), 17-35. https://doi.org/10.1509/jmkg.64.4.17.18077

Roberts, M. L., & Zahay, D. (2018). Internet marketing: Integrating online and offline strategies (4th ed.). Cengage Learning.

Rust, R. T., Lemon, K. N., & Zeithaml, V. A. (2004). Return on marketing: Using customer equity to focus marketing strategy. Journal of Marketing, 68(1), 109-127. https://doi.org/10.1509/jmkg.68.1.109.24030

Schmitt, P., Skiera, B., & Van den Bulte, C. (2011). Referral programs and customer value. Journal of Marketing, 75(1), 46-59. https://doi.org/10.1509/jm.75.1.46