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Record W2278479652

To Grow Profitably, Manage Customer Value, Not Customer Relationships

2003· article· en· W2278479652 on OpenAlexaboutno aff
E. Armour, Lee Mergy

Bibliographic record

VenueThe Journal of Bank Cost & Management Accounting · 2003
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCustomer Service Quality and Loyalty
Canadian institutionsnot available
Fundersnot available
KeywordsCustomer profitabilityBusinessCustomer retentionCustomer equityMarketingShareholder valueCustomer to customerCustomer lifetime valueCustomer delightCustomer advocacyProfitability indexFinanceFinancial institutionLiberian dollarReturn on investmentShareholderEconomicsCorporate governanceMicroeconomicsProfit (economics)Service (business)
DOInot available

Abstract

fetched live from OpenAlex

It's a zero-sum game and the clock is ticking, but only a few players have the right 'play book.' Senior executives at virtually every major financial institution are frustrated. They have seen minimal return on huge investments in customer relationship management - well over $2 billion annually in the United States alone.1 Often the return on these investments hasn't covered their dollar cost or the opportunity cost of management time and energy, let alone provided an adequate return to shareholders. Yes, there have been a few success stories, but for the most part these investments have been disappointing. Consequently, in a period of slow economic growth and intense profitability pressures, many companies are facing a key strategic choice: whether to continue investing in CRM - and, if so, how? We believe that customer management initiatives have the potential to drive tremendous improvements in profitable growth and warrant continued investment by many large financial institutions. But most firms must take a dramatically different approach if they want to create true strategic advantages. Companies unwilling or unable to change their traditional approach are likely to lose (gradually at first and more rapidly in three to five years) their ability to retain their most profitable customers and generate reasonable shareholder returns. First and foremost, they must shift their frame of mind from managing customer relationships to managing customer value. Managing customer value is a two-way street: It entails managing both the value provided by the company to customers and the value of customers to the company. Decisions are based on a detailed understanding of the value that customers place on the benefits they receive and on the economics of delivering those benefits. In this article, we address four questions that executives should ask themselves when considering additional investment in customer management initiatives: 1. Can I deliver meaningful profitable growth through a more systematic management of my customer relationships? 2. What constraints are keeping me from translating this customer value into value for the company? 3. How should I best pursue future investments in managing customer value? 4. Are there natural next steps I can take today to advance my company's capabilities? Profitable Growth Potential The profitable growth potential (top-line and bottom-line) of improved customer management is particularly large in financial services. Analysis has shown time and again that the economic profits (net income less a charge for equity capital employed) of financial institutions are highly concentrated in the top two to three deciles of customers. In many businesses, the top decile alone accounts for more than 50% of total economic profits. Enriching the customer mix toward the more profitable deciles, reducing the numbers of unprofitable customers and capturing a greater share of total customer spending have all proven to be powerful ways of increasing long-term intrinsic value. Can these opportunities be more effectively pursued through a customer value approach? Several early leaders have reported major improvements in performance. Royal Bank of Canada is considered a pioneer in customer value management, and its returns to shareholders have substantially exceeded the S&P 500 Financial Index over the past five years, creating an additional $8.6 billion in shareholder wealth. Although the bank is fairly tightlipped about its success, it has cited an increase in its direct-marketing response rate to as much as 40%, compared to a 2-4% average across industries. The National Australia Bank has also demonstrated dramatic improvements in performance from its early initiatives, with customer penetration and share of wallet in the small business sector rising to market-leading levels of 31% and 77%, respectively. …

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.045
Threshold uncertainty score0.150

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.004
Scholarly communication0.0160.014
Open science0.0010.005
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0450.039

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.040
GPT teacher head0.263
Teacher spread0.224 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2003
Admission routes1
Has abstractyes

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