Marketing Week 5

Bens and Dubois, 2014

L’Oréal struggling to identify new product opportunity despite its reputation for being innovative. VP of Global Integrated Comms = convinced social media could be key. Consumer Products Division controlled 3 main lines – L’Oréal Paris, Garnier and Maybelline. 3 main hair colour categories – temporary, semi-permanent and permanent. Permanent – largest share but demand for temporary and semi-permanent = rising.

Customer motivation for hair colouring - Covering grey hair = 70/80% market. To increase self-confidence = 2ndy highest reason. 88% of women felt hair colouring increased their self-confidence. Until 2011 reason for dying hair = function – not just for fun/to feel good.

Challenges - Distinguish fads and trends = key challenge in the beauty industry. Fads = fast rise and quickly burn out – trends last longer and have the potential to become ‘classics’. Ombre trend emerging among celebrities was noticed + more ‘out there’ celebs like Nicki Minaj used tie-dye/rainbow hair. 3rd trend – ‘splat hair’ bright colours. Social media =opportunity for companies to have quicker access to consumer data allowing firms to better distinguish trends and fad.

Working with Google, L’Oréal Paris began to systematically incorporate google research when looking into information related to hair dye. Whilst both ombre and tie-die had strong data – the qualitative information was telling a different story. Whilst magazines claimed ombre was over there were lots of how-to videos at home

Marking to push the products  - options = Create pages for the brand – Facebook, twitter etc, Find consumers willing to start a buzz. Build a platform for consumers to exchange information and give tips.

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Ofek, 2014

Realisation of importance of understanding customers quantitative perspective rather than just a qualitative has been driven by greater availability of ‘hard data’ on individuals. Customer Lifetime value (CLV) – each customer viewed like a financial asset that will yield recurring net cashflows. Customer value is assessed in today’s monetary lens must be discounted to each future net cash flow using the appropriate cost of capital. CLV useful for getting an understanding of expected profits from a given customer but is an absolute measure. Customer Lifetime Return on Investment (CLROI) - Used to assess how financially attractive customers are by looking at the return from an initial upfront investment.

Not all customers are created equal – customers have different “needs, desires, buying behaviour, ability to pay, and product/service usage patterns overtime” -P.5. Segmentation allows potential customers to be split into groups that are more homogeneous especially their lifetime value parameters. While absolute values may initially seem more attractive often ROI shoe that other assets are more attractive.Often CLV and CLROI measures favour the same segment but don’t always coincide

Segmenting = more complex than these measures but using these or at least including them will help firms  make these choices. But there are some factors that must be considered. Looking at potential customers must remember that these customers must then be converted into actual customers. Only a subset of potential customers progress through each stage of the ‘conversion funnel’. Assumed that lifetime value parameters  constant – variation cancel each other out therefore on average they are constant is seemingly reasonable.No parameters = immune to change overtime particularly Acquisition Cost (AC) as this plays a key role in determining the value of the quantity and  (especially with new products) shows directional patterns of change over time. May be better to mix and match from multiple segments.

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Avery et al, 2011

Customers = assets. 3 methods of customer management: Asset acquisition – attracting new customers; Asset maximisation – maximising value extracted from each customer and Asset retention – retaining existing customers long term.

CLV allows managers to understand value of customer base and assess management strategies. Depends on;  the cost to acquire the customer, the annual profits the customer generates and the number of years the customer is likely to purchase form the firm. Basic CLV formula – CLV = m*L – AC [ m = contribution margin generated by a customer in a year, L = expected purchasing life of customer and AC = up front cost of acquiring customer] Valuable customer = cheaper, generate more profit and choose to be customers for a long time. Model assumes that profits generated by customer which are same in each period and it doesn’t take into account time value of money – 0 discount rate.

Other useful metrics include: CR (churn rate) = % of customers who end their relationship with a company in a given period; RR (retention rate) - % customers who continue their relationship with the company; s (survival probability) – probability customer has a relationship with a firm = 1 in period customer joins firm and then changes in each subsequent period and L (expected purchasing life) – number of periods customer is expected to constitute the relation ship if churn and retention rates for change over time and that its possible for a customer to remain for an infinite time horizon.

Managers use CLV to calculate lifetime value of different market segments and use CLV analysis to inform marketing decisions. Primary Decision areas = type of cusotmer segmetn to target; tp scale up/down marketing expenditures for a partiuclar cusomter, to decide when to fire a customer and  how much to spend to acquire and retain customers.

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Oliver, 1993

Abstract - An attempt to extend current thinking on post-purchase response to include attribute satisfaction and dissatisfaction as separate determinants not fully reflected in either cognitive (i.e., expectancy disconfirmation) or affective paradigms is presented. In separate studies of automobile satisfaction and satisfaction with course instruction, respondents provided the nature of emotional experience, disconfirmation perceptions, and separate attribute satisfaction and dissatisfaction judgments. Analysis confirmed the disconfirmation effect and the effects of separate dimensions of positive and negative affect and also suggested a multidimensional structure to the affect dimensions. Additionally, attribute satisfaction and dissatisfaction were significantly related to positive and negative affect, respectively, and to overall satisfaction. It is suggested that all dimensions tested are needed for a full accounting of post-purchase responses in usage.

Summary - “This study both extends and departs from prior work on the role of affect in the consumption experience in a number of ways.  It confirms the existence of positive and negative affect in consumption, corroborates the degree to which affect appears to be a response separate from disconfirmation, and supports the indirect mechanism of the attribute basis of satisfaction, which suggests a mechanism by which affective response mediates the effects of the attributes on satisfaction. Thus, the attribute influences, the influence of positive and negative affect, and the disconfirmation coefficients point to complexity in the satisfaction formation process not yet fully understood; additional work in the area is needed to address this complexity” – p.429

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Reichheld, 2003

Despite the fact firms often invest lots of time and money into measuring satisfaction many of the measures are complex and lead to ambiguous results that don't necessarily correlate with actual profits or growth. A better approach is to. Ask consumers whether they would recommend allows you to measure how many ‘promoters’ you have - more promoters = more growth. Willingness to promote indicates loyalty as when customers recommend you they are willing to put their own reputations on the line and they would only take this risk if they were intensely loyal.

Calculating net promoter score (ratio of promoters to detractors) - 9-10 -promoters, 7-8 positively satisfied and 0-6 – detractors. Using this score will provide useful insight into how to get more promoters and fewer detractors.E.g. comparing companies score region to region or branch to branch etc to uncover root causes of differences and share best practices. Surveying competitors customers using the same method can also be helpful

The score can be used to send a clear message to managers and employees  - the importance of promoters. Guidelines for doing so –  Ensure employees understand what they are responsible for and that all functions own and accept the survey’s process and results + Make scores transparent (create a sense of urgency by tying rewards to score improvement).

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Shah et al., 2006

Until the information technology revolution in the second half of the 20th century firms tended to be more product-centric. Profits were usually a reflection of market share meaning economies of scale and scope were important. This led to firms becoming more intrinsically focused on manufacturing a superior product rather than meeting consumer needs. This changed when after the information technology revolution as firms had better ways of collecting and analysing vast amounts of customer information and so began to focus on customer relationships 

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Recihheld, 1996

A simple example of a customer centric approach is a customer-led approach. Whilst this approach is seemingly limited, in a fairly stable environment being ablw to respond quickly to changes in consumer needs can be a significant competitive advantage 

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Andreassen et al., 2008

found that the NPS metric performed badly only explaining 0-20% of customer behaviour

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Slater and Narver, 1998

Amongst the literature, there is not one definition of what customer centricity is. The key themes are that the focus is on meeting the customers’ needs. A customer centre business is focused on understanding the wants and needs expressed by customers in a segment and meeting those needs 

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When Canon first introduced the personal copier it was not to meet a consumer need. In fact, many couldn’t understand why anyone would need the product. But by focusing on the product they were able to create a new market. Initially it seems that Canon was product-oriented rather than focused on customer specific needs. On the other hand, arguably, the firm was focused on consumer’s future or unexpressed needs.

First Union Bank uses a database technology known as “Einstein” to colour code its customers. Green customers are profitable and receive extra customer service support . Red customers lose money for the bank and are not granted any special privileges or fee waivers 

L’Oréal successfully used consumer data and a customer centric approach to target a new segment by working with google to analyse information from internet and social media. They were able to combine data with qualitative information to create innovative products that met unmet needs, such as a home ‘ombre hair’ kit. They also used the social media where trend was spotted to advertise the brand through YouTube and Facebook ‘how-to videos. Given their previous products if they had not focused on the customer information, they were unlikely to develop these products. Whilst customer centricity was successful here the approach to assessing consumer needs will affect the effectiveness of customer centricity. For instance, if L’Oréal had looked at the quantitative information alone it would have been harder to assess what is a trend and what is a fad. The firm used customer centricity to direct its product development

Monzo - Creates Loylaty - focused socail media + aim to make finances hassle free. Convicnes consumers that the company's success is also their success. Also highlights number of crowd funders/everyday investors etc - again adding to the community feel.

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Stephen, 2017

UK retail banking market was utility-like with low levels of innovation, differentiation and growth. In addition, customer service was poor throughout this industry resulting in low customer satisfaction. Metro Bank uses a customer-centric model with the aim of creating “fans not customers” by creating standardised aspects of customer experience that improve customer satisfaction.

The more practical improvements include 77% of accounts open in just 15 minutes and having safety deposit boxes in all stores. But they also focus on more experiential factors such as employees being discouraged form saying ‘no’ (to say no two employees must agree) and removing “stupid bank rules” such as restrictive inflexible opening times.

The bank was founded in July 2010 and by the end of 2016 it had 48 stores. This customer-centric has led to significant growth and success for Metro Bank.

the NPS metric is a key part of Metro Banks ‘creating fans’ approach which was very successful. 

More recently the bank has faced financial issues as customers withdrew £2bn of deposits in the first six months of 2019 in response to a misreporting scandal. The bank miscategorized a large number of loans => bank did not hold enough capital, forcing it into a £375m fundraising in May (Crow, 2019) - David Crow Financial Times July 2019

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Keiningham et al., 2008

First, forward-looking customer metrics focused on why people buy - a matter of marketing. 70/80s realisation that overall customer experience was important. SERVQUAL scale developed in the mid-80s by Parasuraman, Zeithaml and Berry examined multiple dimensions of service quality in terms of 5 core constructs = Tangibles, reliability, responsiveness, assurance and Empathy. 90's focus shifted to customer retention leading to NPS.

NPS focuses on how customer word of mouths (WOM) can advance growth. NPS survey how likely are you to recommend this company on a scale of 1 to 10. Promoters – the rate at 9-10 Detractors are those that rate 6 or below. (NPS – percentage of promoters – percentage of detractors).Attractive measure due to its simplicity + research supporting high NPS score and high growth rates. E.g. highest NPS in an industry => growth rates 2.5 times high than those of competitors on average

K's Study aimed to replicate results using the methodology in Reichheld’s research on NPS but found other measures were better at measuring different aspects of loyalty (Best predictor of share spending = past share spending; Best predictor of retention was repurchase intention;  Best predictor of recommendation = recommendation intention (RI foundation of NPS))

A strong link between NPS and loyal behaviour was not found. It was also found to not be a strong predictor of growth being the best predictor in just 2 out of 19 cases. Managers that use the NPS may have unrealistic perceptions about performance, value and shareholder wealth that may lead them to misallocate resources. There are many factors that affect customer loyalty and its impact on con customer behaviour and resulting growth and financial success. Instead of just relying on NPS managers need to accept that metrics are tools to assist them in making decisions but cannot make the decision for them Further analysis is essential to make good decisions.

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