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2023 | OriginalPaper | Buchkapitel

13. From Market Research to Product Positioning

verfasst von : Marco Cantamessa, Francesca Montagna

Erschienen in: Management of Innovation and Product Development

Verlag: Springer London

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Abstract

This chapter discusses the main topics pertaining to the front end of a product development process, starting from the definition of the market, going through a systematic understanding of customer needs in both B2C and B2B contexts and achieving a solid positioning with respect to customer perception and pricing. Then, the chapter discusses the issue of forecasting demand, with a special focus on the case of estimating diffusion phenomena for new technologies and associated market shares. This latter discussion will build on classical models from Bass and Kotler, and add recent research findings.

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Vorheriges Kapitel Project Management for Product Development

Nächstes Kapitel Specifying the Product

For the time being, we will use the term ‘customer’ in a very broad sense, including any actor that has a role in purchasing and then using the product or service. We will later be more precise in discussing how the purchasing and usage processes include multiple actors, which will have to be considered separately and in their interactions.

In the case of fine mechanical watches with multiple ‘complications’, for instance, customers are willing to pay significant amounts of money for an object that is at the same time a status symbol, the fruit of high-end technology and engineering skills, as well as an object of art. Similarly, most new products in the automotive industry can be associated to design-driven innovations, since aesthetic and cultural aspects have a role that is comparable—if not even superior—to vehicle performance and satisfaction of functional needs.

As an example, one can think of the lack of communication between a producer of toothpaste, and the millions of people who daily purchase this product, and then compare it to the continuous interchange of information between the producers of specialized machine tools and their few and well-known customers.

A hierarchical coding of economic activities is composed by a string of characters, with the first ones representing the higher-level classification and the subsequent ones representing finer subdivisions whose meaning depends on the former. So, for instance, NACE C13.9.3 defines ‘manufacturers of carpets and rugs’, with C representing all kinds of ‘manufacturing’, C13 the ‘manufacture of textiles’ and C13.9 the ‘manufacture of other textiles’.

For instance, a firm may define its market as the ‘market for urban mobility’ and develop a product for the segment of ‘city bicycles’. Another firm may instead define its market as ‘bicycles’ and operate on the segment of ‘road bicycles’.

The Hierarchy of Maslow* has been questioned by later research under a number of perspectives; nevertheless, it still remains a recognized reference for marketing applications.

For instance, imagine a person having to choose a TV set in a store. Dozens of models are on display, each of which carries an information card that lists a dozen features or so, together with price. It would be unlikely to see that person make a choice by pulling out a sheet of paper, writing down a shortlist of TVs that exceed given thresholds, and then ranking them based on a weighted score of performance indicators. This will not happen because of two reasons: technical features alone are not enough to drive the purchasing process, and humans are not able to manage multiple dimensions in decision making.

An example of perception has to do with reading. Reading this book means that your eyes are stimulated by light patterns corresponding to the characters on the page. A perceptual process allows you to isolate the characters, understand them, aggregate them in words and—hopefully—understand their meaning. The perceptual process is not innate and has to be learned, and the information thus processed can be managed only in relation to pre-existing knowledge and experience (think about the difficulty in reading a book on a familiar subject, written in an unfamiliar language, or even written with uncommon fonts).

For instance, the digital cameras of the previous example may be perceived and assessed by consumers according to two dimensions, such as ‘technical performance’ and ‘ease of use’.

Before reading further, try reflecting on a recent and infrequent purchase you may have made (i.e., a relatively expensive durable product, or a consumable product that you have never bought before). Try listing the sequence of actions and thoughts that led you from the initial stage of ‘I wasn’t even thinking of buying X’ all the way to actually making the purchase. What differences would there be between X being a car, a smartphone or new brand of toothpaste?

This perspective has been discussed in a variety of contexts, such as B2C (Temkin 2010; Lemon and Verhoef 2016), B2B (Hague and Hague 2018; Lecoeuvre et al. 2021) and multi-channel (Barwitz and Maas 2018).

For instance, one may define ‘Marie, 35-year old IT professional, mom of two children (4-year old Susie and 2-year old Jean). She is the wife of Robert, an airline pilot who is often away from home. They live in an apartment in the XV Arrondissement of Paris’. To the family, one may add ‘Jeanne, Robert’s 70-year old mother, who lives close to Robert and Marie and sometimes borrows their car to visit her friends during the weekend’.

For instance, marketing employees of a firm dealing with shaving tools may identify two personas such as ‘John, a bearded man’ and ‘Arthur, a well-shaven man’.

In the case of HVAC systems for residential use, a firm may use personas to represent the target customer, the architect managing the renovation project and the technician that will be in charge of the installation.

In the shaving tool example, a designer will certainly use more than one persona per category. For instance, bearded men will include ‘John the hipster, proud of his beautiful beard, interested about its softness and beauty’ and ‘Dave, who sports a short beard and is not willing to spend much time on it, but cares that the cut is precise and symmetrical’. Shaven men will include ‘Arthur, a 40-year-old who shaves daily but, being in a hurry, often misses the razor at home when he travels’, and ‘Harry, a 70-year-old man with brittle skin’.

From a marketing perspective, this finer distinction would be irrelevant and even misleading, since the objective of market research is to identify market segments (and associated personas) through data analysis, and not to define them ex ante.

The discussion on the nature and the validity of personas is in fact quite present in the literature. Some scholars (e.g., Chapman and Milham 2006) consider them as fictional and not based on a sufficiently rigorous method, since they do not have a clear relationship to actual customer data and do not follow reproducible analysis procedures. The distinction we made in the text between preliminary personas used to support market research and more precise personas to be characterized after market research is carried out goes in the direction of a stream of literature that suggests the usage of data-driven (or quantitative) personas (e.g., McGinn and Kotamraju 2008).

For instance, in the case of a public transport bus, the buyer is the purchasing office of a municipal transport authority, the users will be bus drivers and maintenance crews, and the beneficiaries the passengers who ride the bus. Outsiders include citizens being affected by the emissions of the vehicle, or pedestrians who may be impacted by the bus in case of an accident.

In the case of an electric toothbrush for children, the parents are both customers and beneficiaries, the child is both user and beneficiary, and the dentist is the outsider.

Referring to the public transport example, it is obvious to assume that—all the rest being equal—purchasing managers will prefer a bus that minimizes harmful emissions, even without being directly influenced by citizens. However, the importance that management will attach to this need may be altered if citizens actively cast such an influence through a citizens-rights association.

It is interesting to observe salespeople interact with product development teams and notice that a common question is ‘the features you are proposing for this product are cool, and they might be helpful for our customers, but how are we going to sell them?’ This type of thinking may both guide minor decisions in the design of the product and strategic change in the firm’s business model. For instance, should it become apparent that stakeholders are not willing to accept a product that requires a significant up-front investment (CAPEX) in exchange for reduced operational costs later on (OPEX), the firm may adopt an ‘as a service’ model. This often occurs for energy saving devices in buildings, medical equipment in hospitals, etc.

For instance, a new bus that comes with a powerful but difficult-to-use IT-based fleet management system will probably not be adopted, because drivers will object to the procurement office and oppose the purchasing decision, or may simply avoid using it once it has been bought. Conversely, a system that is user-friendly but expensive will probably be vetoed by managers even if drivers push for its adoption, unless the latter are able to show that it will lead to financial benefits that out-weight the additional cost.

Lead users (Von Hippel 1986) are customers who face needs that will become prevalent much earlier than the general population, and which might contribute with original solutions to solve the need. Following a more extended meaning, a lead user may be a user whose particularly intense usage of the product amplifies her/him perceived needs (for instance, a taxi driver can be considered to be a lead user when it comes to driving a car in an urban environment).

For instance, a focus group participant might say he/she needs her/him smartphone to be equipped with a low-power chipset. Since this is not a need but a technical solution, the analyst should ask her why. The customer’s answer might be that she/he needs her/him phone to have 250 h of standby time between recharges but—again—this is not a need, but a performance specification. So, the analyst will have to ask a second ‘why’, to which the user might answer that she/he basically wants her/him phone battery to last over a weekend, should she/he forget to bring the charger with her/him. This can finally be considered as a need, since it clearly shows an outcome (i.e., a job to be done) that might satisfy the user, regardless of the technical means with which it is achieved.

A firm providing a digital service can easily monitor detailed user activity on a website or a smartphone app, looking at access in general, and at the usage of individual functions (including frequency of use, sequence with which they are run, timing with which actions are carried out, mistakes made, etc.). Sensors in a service environment (e.g., cameras in retail outlets) can capture data on the way people navigate in the physical space and act. Sensors on a product (e.g., the ECUs in a car can capture myriad information on driving habits and mission profiles).

In this case, a key connection is established between the activities that have to do with web, digital and social media marketing and the product development process.

As stated in the introduction, we have chosen not to provide explanations for basic multivariate analysis techniques in this textbook. We therefore suppose that readers are either already familiar with them, or they will be able to refer to specialized sources (e.g., Johnson and Wichem 2007) to gain the necessary knowledge of these techniques and of the way they can be used.

Readers can be referred to Bradburn et al. (2004) or Brace (2008) for an in-depth presentation of this important part of market research.

In other words, in an ordinal scale we know that ‘2’ means more than ‘1’. However, we cannot be sure that the distance between ‘2’ and ‘1’ is the same as between ‘5’ and ‘4’ (which would be true in an interval scale).

For instance, Factor Analysis may show high loadings on the same factor for the three secondary needs ‘I can use my device with one hand’, ‘I can learn how to use my device quickly’, ‘if I make a mistake, my device warns me’. The analyst may interpret this latent variable as representing a primary need that can be named ‘ease of use’.

The literature on optimal pricing is a key topic of both Industrial Economics and Marketing and, due to its vastness, it cannot be effectively summarized here, since it depends on the type of goods and the type of competition in the industry. Beyond the few words that have been spent here, it is convenient to remember that many goods and services require specific highly pricing strategies. Among them one can list experience goods (i.e., goods whose quality can be appreciated only after they are purchased; Shapiro 1983) and Veblen goods (i.e., ‘luxury’ goods, whose demand rises with price; Huang et al. 2017).

As an example of cannibalization, think of a luxury car manufacturer that starts selling compact cars alongside to traditional sedans, and discovers that customers of the latter are moving to the cheaper model.

In 1849, the French economist Jules Dupuit (1804–1866) noticed that railways companies were purposely making third-class carriages uncomfortable not to reduce cost, but in order to ‘scare away’ customers who had enough money to buy second- and first-class tickets.

The two parameters are not symmetrical and depend on the specific products. For instance, in the case of BEVs and domestic recharging stations, it is likely that the former will drive the latter (i.e., people who buy a BEV will tend to buy a wallbox charger for their garage), and not vice versa. In fact, few people would buy a BEV because they have bought a wallbox charger for their garage, or because they have found one when purchasing the garage. On the opposite, in the case of BEVs and street-based recharging stations, the latter will quite heavily drive the former (i.e., people will buy BEVs when enough chargers are visible on the streets) and the former will somewhat drive the latter (i.e., recharging service operators will adapt their offer by observing the diffusion of BEVs).

Barwitz N, Maas P (2018) Understanding the omnichannel customer journey: determinants of interaction choice. J Interact Mark 43(C):116–133

Bass FM (1969) A new product growth for model consumer durables. Manag Sci 15(5):215–227MATHCrossRef

Bass FM, Krishnan TV, Jain DC (1994) Why the Bass model fits without decision variables. Mark Sci 13(3):203–223CrossRef

Box GEP, Jenkins GM, Reinsel GC (2008) Time series analysis: forecasting and control. Wiley, New YorkMATHCrossRef

Brace I (2008) Questionnaire design: how to plan, structure and write survey material for effective market research (market research in practice). Kogan Page Ltd., London

Bradburn NM, Sudman S, Wansink B (2004) Asking questions: the definitive guide to questionnaire design—for market research, political polls, and social and health questionnaires. Jossey-Bass Publishers, San Francisco

Brunswik E (1944) Distal focusing of perception: size constancy in a representative sample of situations. Psychol Monogr 56:1–49CrossRef

Cantamessa M, Montagna F (2016) Design for innovation—a methodology to engineer the innovation diffusion into the development process. Comput Ind 75:46–57CrossRef

Cantamessa M, Montagna F, Cascini G (2012) Design for innovation. In: The 12th international design conference design 2012, Dubrovnik, Croatia, 21–24 May

Cantamessa M, Montagna F, Messina M (2013) Multi-stakeholder analysis of requirements to design real innovations. In: 9th International conference on engineering design (ICED09), Stanford, California, 24–27 Aug

Cascini G, Montagna F (2015) Situating needs and requirements in a multi-stakeholder context. Design Computing and Cognition (DCC 14), London, UK, 21–22 June

Chapman CN, Milham R (2006) The personas’ new clothes: methodological and practical arguments against a popular method. Hum Factors Ergon Soc Annu Meet 50(5):634–636CrossRef

Chun SY, Hahn M (2008) A diffusion model for products with indirect network externalities. J Forecast 27(4):357–370MathSciNetCrossRef

Cooper LG, Nakanishi M (1988) Market share analysis. Kluwer, LondonCrossRef

Decker R, Gnibba-Yukawa K (2010) Sales forecasting in high-technology markets: a utility-based approach. J Prod Innov Manag 27(1):115–129CrossRef

Fourt LA, Woodlock JW (1960) Early prediction of market success for new grocery products. J Mark 25:31–38CrossRef

Fuchs C, Schreier M (2011) Customer empowerment in new product development. J Prod Innov Manag 28(1):17–32CrossRef

Giovanis AN, Skiadas CH (2007) A new modeling approach investigating the diffusion speed of mobile telecommunication services in EU-15. Comput Econ 29:97–106MATHCrossRef

Gray D, Brown S, Macanufo J (2010) Gamestorming: a playbook for innovators, rulebreakers, and changemakers. O’ Reilly, Sebastopol, California

Gupta S (1991) Stochastic models of interpurchase time with time-dependent covariates. J Mark Res 28(1):1–15CrossRef

Helsen K, Schmittlein DC (1993) Analyzing duration times in marketing: evidence for the effectiveness of hazard rate models. Mark Sci 12(4):339–427CrossRef

Hague N, Hague P (2018) B2B customer experience: a practical guide to delivering exceptional CX. Kogan Page, London

Horsky D (1990) The effects of income, price and information on the diffusion of new consumer durables. Mark Sci 9(4):342–365CrossRef

Hotelling H (1929) Stability in competition. Econ J 39(153):41–57CrossRef

Huang A, Dawes J, Lockshina L, Greenacre L (2017) Consumer response to price changes in higher-priced brands. J Retail Consum Serv 39:1–10CrossRef

Jain CL, Malehorn J (2005) Practical guide to business forecasting. Graceway Publishing Company, New York

Johnson R.A., Wichem D.W. (2007), Applied Multivariate Statistical Analysis, Pearson Education, Edinburgh.

Kano N (1984) Attractive quality and must be quality. Hinshitsu (Quality) 14(2):147–156

Kiesling E, Günther M, Stummer C, Wakolbinger LM (2012) Agent-based simulation of innovation diffusion: a review. CEJOR 20(2):183–230CrossRef

Krishnan V, Zhu W (2006) Designing a family of development-intensive products. Manag Sci 52(6):813–825CrossRef

Landsman V, Givon M (2010) The diffusion of a new service: combining service consideration and brand choice. Quant Mark Econ 8:91–121CrossRef

Lecoeuvre L, Turner R, Kuppelwieser VG (2021) Customer experience in the B2B area: the impact of age-related impressions. J Retail Consum Serv 58:102216CrossRef

Lemon KN, Verhoef PC (2016) Understanding customer experience throughout the customer journey. J Mark 80(6):69–96CrossRef

Levinthal DA (1997) Adaptation on rugged landscapes. Manage Sci 43(7):934–950MATHCrossRef

Libai B, Muller E, Peres R (2009) The diffusion of services. J Mark Res 46(2):163–175CrossRef

Lin C-S (2013) Forecasting and analyzing the competitive diffusion of mobile cellular broadband and fixed broadband in Taiwan with limited historical data. Econ Model 35:207–213CrossRef

Mahajan V, Muller E, Wind Y (2000) New product diffusion models. International series in quantitative marketing. Kluwer Academic Publishers, London

Makadok R, Ross DG (2013) Taking industry structuring seriously: a strategic perspective on product differentiation. Strateg Manag J 34(5):509–532CrossRef

Mansfield E (1961) Technical change and the rate of imitation. Econometrica 29:741–766MATHCrossRef

McGinn J, Kotamraju N (2008) Data-driven persona development. In: SIGCHI Conference on human factors in computing systems (CHI’08). Association for Computing Machinery, New York, NY, USA, pp 1521–1524

Monat JP (2011) Industrial sales lead conversion modeling. Mark Intell Plan 29(2):178–194MathSciNetCrossRef

Moorthy KS, Png IPL (2002) Market segmentation, cannibalization and the timing of product introductions. J Manag Sci 38(3):345–359MATH

Phillips H, Bradshaw R (1993) How customers actually shop: customer interaction with the point of sale. J Mark Res Soc 35(1):51–62

Prasad RK, Jha MK (2014) Consumer buying decisions models: a descriptive study. Int J Innov Appl Stud 6(3):335–351

Puccinelli NM, Goodstein RC, Grewal D, Price R, Priya RP, Stewart D (2009) Customer experience management in retailing: understanding the buying process. J Retail 85(1):15–30CrossRef

Ratchford BT, Balasubramanian SK, Kamakura WA (2000) Diffusion models with replacement and multiple purchases. In: Mahajan V, Muller E, Wind Y (eds) New product diffusion models. Kluwer Academic Publishers, Boston

Saha A, Hilton L (1997) Expo-power: a flexible hazard function for duration data models. Econ Lett 54(3):227–233MATHCrossRef

Satoh D (2001) A discrete bass model and its parameter estimation. J Oper Res Soc Jpn 44(1):1–18MathSciNetMATH

Seetharaman PB, Chintagunta PK (2003) The proportional hazard model for purchase timing: a comparison of alternative specifications. J Bus Econ Stat 21(3):368–382MathSciNetCrossRef

Shapiro C (1983) Premiums for high quality products as returns to reputations. Q J Econ 98(4):659–679CrossRef

Shi X, Chumnumpan P, Fernandes K (2014) A diffusion model for service products. J Serv Mark 28(4):331–341CrossRef

Tapp SR (1984) Brunswik’s lens model: a review and extension to consumer research. Adv Consum Res 11:103–108

Temkin BD (2010) Mapping the customer journey. Forrester Research Inc.

Van Westendorp P (1976) NSS-price sensitivity meter (PSM)—a new approach to study consumer perception. 29th ESOMAR congress, Venice, Italy

Verganti R (2009) Design driven innovation: changing the rules of competition by radically innovating what things mean. Harvard Business Press, Boston

Vinokurova N (2019) Reshaping demand landscapes: how firms change customer preferences to better fit their products. Strateg Manag J 40(13):2107–2137CrossRef

Von Hippel E (1986) Lead users: a source of novel product concepts. Manag Sci 32:791–805CrossRef

Titel: From Market Research to Product Positioning
verfasst von: Marco Cantamessa
Francesca Montagna
Verlag: Springer London
Buch: Management of Innovation and Product Development
Print ISBN: 978-1-4471-7530-8

Electronic ISBN: 978-1-4471-7531-5

Copyright-Jahr: 2023
DOI: https://doi.org/10.1007/978-1-4471-7531-5_13

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