Area of Influence
The concept of market penetration depends on the definition of an area of influence, the space where the store will be competitive in its offers.
There is a maximum range, which varies depending on the target activity.
Bakeries are convenience operations, so consumers will value proximity, with a point of disinterest depending on the distance between the consumer and the bakery.
Between that maximum distance point that leads to disinterest and the prairie, an area is formed, which we call the area of influence.
Given its set of options, the consumer will choose the place where they will make their purchases.
Consumer preferences and behavior patterns define areas of influence.
Consumer surveys - direct surveys regarding the purchase reasons, preference criteria, and travel to that point.
The David L. Huff model expands on the work of William J. Reilly, assuming the attractiveness of a store based on its gravitational force, which increases as the store offers more shopping options.
Professor Juracy Parente revisited the main theories in a study he analyzed The catchment area of supermarkets in São Paulo and confirmed its validity in the Brazilian market.
After mapping and analyzing the geospatial distribution of customers around the supermarkets, he divided the concept of Area of Influence into three parts:
- Primary - reach corresponding to 75% of customers
- Secondary - reach corresponding to 15% of customers
- Tertiary - range corresponding to the remaining 10%
Today, we recommend treating the area with up to 80% of clients as the space of influence and leaving the rest as a complement.
Behind this simplified logic is the understanding that, in these more remote spaces, the store should not direct efforts to increase its sales.
Market Penetration
It is in the region of primary influence that a store will have the most strength to attract a greater proportion of customers, that is, to increase its market penetration.
Therefore, if there is a population of ten thousand people and the store serves two thousand, there will be space to attract more customers in that same area.
Billing Potential
Comparative methods use a similar existing location where a store already exists to project sales.
If they are not so similar, it is also possible to adjust expectations in relation to differences.
Other adjustments may come from gravitational analyses that take into account attractiveness, generally a measure proportional to the sales area and its diversity of categories, and other aspects such as visibility, accessibility, and the presence of synergistic operations.
Finally, potential reducers can be applied that consider the distance of the store from consumers, the type of location in which it is located, and the presence or absence of competitors.
Summary
The most consolidated practices involve mapping customer data in order to visualize where customers are located, in contrast to layers of demographic, economic, and competitor data for comprehensive analysis.
This analysis of the area of influence involves identifying where a store's customers are coming from and their axes of attraction.
By observing the travel time, it will be possible to understand the customer's travel pattern to the store.
We will then have a well-defined area of influence.
We can now assess market penetration, how much a product or service is being used by customers compared to the total market.
A reasonable market share can be attributed to competitors, resulting in the sales potential available.
Other studies, and complementary research reports can help in understanding the overall dynamics of the market and how market captures can be disputed.
With the market space available for capture delimited, which can be in cash, units, or volume of customers, we set out to capture them.
A good market capture campaign must reflect the consumer's demographic and economic profile.
From then on, it is necessary to monitor the evolution of sales to identify trends and patterns of success.
References
APPLEBAUM W. Methods for determining store trade areas, market penetration, and potential sales. Journal of Marketing Research. May 1966.
SPIDER, Francisco. Atlas of the postal sectors: a new geography at the service of the company. RAE Business Administration Magazine, São Paulo 1997.
BELL, David R., HO, Teck-Hua, TANG, Christopher S. Determining where to shop: fixed and variable costs of shopping. Journal of Marketing Research, Chicago, Aug. 1998.
BERMAN, Barry, EVANS, Joel R. Retail management: a strategic approach. Upper Saddle River: Prentice Hall, 1998.
BLACK, W. Choice-set definition in patronage modeling. Journal of Retailing, Greenwich, 1984.
BOOTS, Barry, SOUTH, Robert. Modeling retail trade areas using High-Order, Multiplicatively Weighted Voronoi Diagrams. Journal of Retailing, Greenwich, Winter 1997.
CLIQUET G. Geomarketing: Methods and strategies in spatial marketing. John Wiley & Sons. 2013.
TALK TO PD. New laws of retail gravitation. Journal of marketing. Oct 1949
CRAIG, C. Samuel, GHOSH, Avijit, McLafferty, Sara. Models of the retail location process: a review. Journal of Retailing, Greenwich, v. 60, No. 1, pp. 5-36, Spring 1984.
DOUARD JP, HEITZ M, CLIQUET G. Retail attraction revisited: From gravitation to purchase flows, a geomarketing application. Research and Applications in Marketing (English Edition). Jan 2015
FURLAN AA. Geoprocessing: Geomarketing studies and the possibilities of their application in socio-economic development planning. GEOUSP: Space and Time (Online). Dec 2011
GHENCEA, Adrian; GAUCAN, Violeta; PIRVU, Daniela. Distributed Systems and Web Technologies. Journal of Knowledge Management, Economics and Information Technology.
GHOSH, Avijit, CRAIG, C. Samuel. FRANSYS: a franchise distribution system location model. Journal of Retailing, Greenwich.
HUFF, David L. Defining and estimating a trade area. Journal of Marketing, New York,
KRUGMAN P. Increasing returns and economic geography. Journal of Political Economy. Jun 1991
LOBBEN A, LAWRENCE M. Synthesized model of geospatial thinking. The Professional Geographer. July 2015
LONGLEY PA, GOODCHILD MF, MAGUIRE DJ, RHIND DE. Geographic Information Systems and Science. Bookman Publisher. 2009.
McGill, Kenneth H. A method for delineating retail trade area. Journal of Retailing, Greenwich,
MIRANDA ART, BENDLIN L, JUNIOR JM. Point of Sale Location—A Case Study on the Use of Geomarketing. Administration Notebook.
O'ROURKE J. Computational geometry in C (Cambridge tracts in theoretical computer science). Cambridge University Press. 1998.
RELATIVE, Juracy. Market performance indicators for supermarkets. London Business School, University of London, 1978. Thesis (Doctorate).
PETERSON, Robert A. Trade area analysis using trend surface mapping. Journal of Marketing Research, Chicago.
REILLY WJ. The law of retail gravitation. W.J. Reilly. 1931.
REILLY, William J. Method for the study of retail relationships. Austin: University of Texas Press, 1929. Research Monogragh No. 4, University of Texas Bulletin, no. 2944, 1929.
RODRIGUE JP, COMTOIS C, SLACK B. The geography of transport systems. Routledge. 2009.
PINK, Roberto. Geotechnologies in applied geography. Journal of the Department of Geography,
SHETH, Jagdish N., MITTAL, Banwari, NEWMAN, Bruce I. Customer behavior: consumer behavior and beyond. Fort Worth: The Dryden Press, 1999.
SIENA SS. The algorithm design manual: Text. Springer Science & Business Media. 1998.
TAYMAN, Jeff, POL, Louis. Retail site selection and geographic information systems. Journal of Applied Business Research, Laramie,
TOBLER WAR. A computer movie simulating urban growth in the Detroit region. Economic geography. Jun 1970
WEBSTER FE, LUSCH RF. Elevating marketing: marketing is dead! Long live marketing!. Journal of the Academy of Marketing Science. July 2013
WU X, KUMAR V, QUINLAN JR, GHOSH J, YANG Q, MOTODA H, Mclachlan GJ, NG A, LIU B, PHILIP SY, ZHOU ZH. Top 10 algorithms in data mining. Knowledge and information systems. Jan 2008
YRIGOYEN CC. Geomarketing and commercial distribution. Research and marketing. Jun 2003