Characteristics of the Pizzeria “L’Olivo”

Tire Italian restaurant and pizzeria “L’Olivo” (L’Olivo Limited Liability Company) specializes in the sale of Italian specialties: pizza and pasta. Food products are purchased from certified suppliers who can document the fact of meeting all required legal standards, Polish and those of the EU. The offer of the restaurant is a proposition of real Italian cuisine and selected wines at available prices.

Hie main source of the company’s revenues is catering, which is characterized by systematic growth on an annual basis. Revenues of the restaurant are characterized by seasonality, which depends, among others, on weather changes and the associated variable number of tables and fewer sales days in the winter months. The highest revenues are achieved in the third quarter and the lowest in the first quarter of the year. When analyzing the cost aspect, attention should be paid to a significant improvement in the restaurant’s work efficiency in recent quarters. The efficiency improvement was influenced by:

■ Price policy. The company has successfully introduced changes in price management. The previous owners introduced the price offer regardless of the perception of the location and groups of consumers using the services of the restaurant. The new management has adapted the offer to various customer segments and thus achieved the appropriate sales volume while maintaining the assumed sales profit.

■ Reduction of other costs. Other costs include telecommunications services, marketing costs, costs of website creation, repairs, and the like. This whole group of costs in relation to revenues is around 15%. In recent quarters, the company has carried out many activities aimed at limiting this cost category, such as renegotiating contracts; rationalizing the costs associated with playing music in the premises; and creating a new website for the restaurant based on a ready WordPress template with further supplementing the content and adapting it to the template layout, choosing photos, and configuring the appropriate layout.

Market position, the current perception of the company by contractors, and the company’s current activities allow the company to acquire more customers, build loyalty in relation to the ability to introduce new products, and maintain the high quality of services.

Hie SWOT analysis concept used (see Table 11.1) was to identify the strengths and weaknesses of the surveyed company and to identify opportunities and threats in its environment. The current situation and future forecast were analyzed. According to the own study, based on IQS data, the biggest competitors are local pizzerias. The company has taken measures to eliminate weaknesses. Hie main barrier to the dynamic development of the premises is the high costs of running a restaurant, and in the event of breaking the barriers to growth, additional marketing and management costs are needed.

Hie financial situation of the company has improved significantly, but the perspective of the next years requires further intensive work on business development. Hie perception of the restaurant in the near future will be influenced by understanding and acceptance of the strategy aimed at safe development, improvement of

Table 11.1 SWOT Analysis of "L'Olivo" Restaurant

Positive Factors

Negative Factors

Internal factors



  • 1. Location of the restaurant for eight years in the same place.
  • 2. Company results enabling further development.
  • 3. High customer loyalty.
  • 4. High customer satisfaction with the service received.
  • 5. A continuous increase in the ratings of customers visiting the restaurant.
  • 6. Efficient management of the offer for clients.
  • 7. Italian products, management, and chef.
  • 8. Favorable conditions negotiated with suppliers of goods from Italy (90% of the offer of the restaurant).
  • 9. Maintaining the right quality of ingredients and dishes.
  • 10. The high commitment of the management in the work of the restaurant.
  • 1. Three times the change of the owner of the restaurant, which makes building the brand difficult.
  • 2. Errors made by previous owners.
  • 3. Waiters rotation.
  • 4. The premises rented for the restaurant, no own premises.
  • 5. Location of the premises, site not visible.
  • 6. The sensitivity of the Polish consumer to prices.
  • 7. Lack of active promotion of the restaurant on social media profiles.
  • 8. Lack of developed marketing plan.
  • 9. Lack of loyalty programs —until now.

External factors



  • 1. Dynamic residential and office development.
  • 2. Crowing customer purchasing power.
  • 3. Crowing demand for goodquality services.
  • 4. Change in clients' eating habits and an increase in the frequency of visits to restaurants.
  • 5. Decrease in unemployment.
  • 6. Crowing consumer optimism.
  • 7. Strengthening of the national currency (PLN).
  • 1. Unfavorable tax changes.
  • 2. Increase in competition in the segment.
  • 3. The growing interest in cooking at home and cheap fast food offers.
  • 4. Increase in rental prices and real estate prices.
  • 5. Increase in loan costs.

Source: Own calculations based on L'Olivo company.

the company’s results and balance, growth rate and quality, effects of promotional activities on social profiles, and implementation of forecasts.

Hie following research methods and techniques were used in the study: in the theoretical part methods of analysis, synthesis, and deduction, whereas, in the empirical part, the methods of statistical, comparative, and economic analysis as well as heuristic techniques. Hie revealed phenomena and results were presented in a descriptive and graphic form.

Digitization and Use of Data on Consumer Behavior in Creating a Personalized Offer

A modern Internet user develops and functions in various areas thanks to data obtained using modern technologies. In a sense, as a species, he has evolved into becoming homo informaticus (EY, 2015). Hie existence of a situation in which recipients have access to almost countless sources of information makes it necessary to develop and improve the skills of selecting and filtering information. Hie dynamic development of information and communication technologies has significantly influenced changes in the gastronomy sector. Acquiring customers and their favor, positive feedback becomes an important element of promotion. Especially in the group of clients of generation Y, who are extremely demanding, among others, to adapt to their needs and lifestyle. This generation actively uses various communities. On Facebook, people aged 15-30 constitute over 60% of all Polish users of this website (Emplo, 2018). Deloitte’s analysis shows that by the end of 2023 in developed countries, over 90% of adults will use SM, the standard of equipment will be elements of artificial intelligence (Doloitte, 2019). This is a clear signal for many brands and industries how to organize communication with this unique generation.

In creating a personalized offer in the studied restaurant, Facebook social networking statistics were used. Hiey concerned the observation of changes in the behavior of portal users during the advertising campaign from May 12, 2019, in order to like the page.

When launching the advertising campaign using Facebook digital technology, the group of recipients, their location (city of Warsaw), and interests were precisely defined. This is extremely important information for any campaign, without which it would not really matter.

Data obtained from Facebook statistics allow tracking user behavior and their location. They also give the opportunity to study the number of recipients of an advertising campaign. In the discussed case, within 14 days, it amounted to 1,963 people, including 66 people who liked the site. From the point of view of creating customer relationships and customizing the offer, other data that can be obtained from Facebook statistics are also important. Hiese include, apart from demographic data, the number of ad displays and devices used by the followers.

Big Data is nowadays a natural resource for organizations, a digital inventory, as well as a detailed look at the past (Conway and Klabjan, 2013)-

Digitization allows to examine the behavior of a selected group of recipients, including socio-demographic variables; optimize the offer and the final product; and create individualized offers.

Research on Consumer Behavior in Creating Strategies for Influencing Purchasing Decisions

Modern consumers, especially representatives of generation Y, are very mindful. Once a consumer, the so-called homo oeconomicus (Latin for economic man), was compared to an efficiently counting calculator making rational and selfish decisions. However, this concept was quickly questioned by the lack of rationality in making purchasing decisions. The mechanisms that increase the customers’ willingness to buy were analyzed. An analysis of the determinants of consumer assessment of the studied restaurant was carried out. All examined variables have shown that clients of the examined object and consumers nationwide identify quality mainly by the taste characteristics of the product.

To check consumer behavior, a series of studies were conducted. As follows from the observation of a person participating directly in the surveyed place, the main determinants of L’Olivo consumers’ loyalty are primarily the quality of dishes, which is the main factor determining a return to L’Olivo, customer service, and the atmosphere prevailing in the restaurant. Digital technologies and statistics of opinions aggregators on enterprises in the catering industry allow to more effectively examine the behavior of a selected group of recipients, including socio-demographic variables, optimize the offer and final product, and create individualized offers.

Analyzing the collected data, it becomes legitimate to state that the main determinant of the impact on purchasing decisions of the customers of the studied restaurant is, above all, maintaining a constant level of quality, including maintaining or improving the organoleptic characteristics of the dishes served, the level of service, and decor of the place.

Based on a comparative analysis of quality measures offered by the examined restaurant and perceived by consumers, it is justified to state that one of the main tasks in creating a strategy to influence consumer purchasing decisions is to disseminate information on the quality of ingredients for served dishes and the highest quality products presented in the offer. These are products with European quality labels DOC (designation of confirmed origin), DOCG (designation of controlled and guaranteed origin, a higher category of wine classification in the card), DOP (protected designation of origin), which constitute the majority of L’Olivo’s offer.

A study of consumer behavior of a selected gastronomic establishment allows defining main determinants of impact on purchasing decisions and enables the creation of strategies to increase consumer confidence in the restaurant, consequently contributing to increased sales. Understanding which data ensure the achievement of business goals, improving customer service can be time-consuming and requires specialized knowledge on statistical correlations. It should be remembered that Big Data are data that are not subject to so-called sampling. They are completely related to the creation of databases thanks to electronic sources. Importantly, their main goal is not a statistical inference (Horrigan, 2013)- Big Data without proper development is not worth much. They gain value only after processing and careful analysis carried out by specialists.

Figures from Big Data analyses can have a very high material value, especially when combined with other data both from inside the organization and from outside (Trajman, 2013). According to many analysts, the value of the global Big Data market is constantly increasing. In 2014, it was about USD 18 billion. Forecasts for 2026 indicate that it will rise to around $ 92 billion (Connick, 2017).

Hiis phenomenon is becoming more and more worrying for businesses, especially because consumers are increasingly aware of the value of their personal data. That is why building relationships with clients and searching for ways to optimize services using analytical tools is becoming increasingly important.


Acquiring loyal customers becomes a real challenge for a company. In this process, important is the efficient management of customer experience at every stage of cooperation and engaging them in the company’s operations (e.g., promotion, development of new products). This cannot be achieved without knowing the clients expectations, needs, and habits (Buchnowska, 2017). Therefore, modern enterprises are almost forced to use systems that support this goal. New technologies and Big Data are helpful in this process. Hie analysis of large data sets through guest reviews on companies in aggregators of opinions such as TripAdvisor, Google, Facebook, Pyszne, and Uber, which are also available to users in the form of mobile applications, has particular potential. Nowadays, digital technologies open new, previously unknown, and inaccessible opportunities to learn about and meet the needs of consumers. Digital technologies and statistics of opinion aggregators on enterprises in the catering industry allow to more effectively examine the behavior of a selected group of recipients, including socio-demographic variables, optimize the offer and final product, and create individualized offers. They have become an inseparable tool for creating strategies for building positive customer relationships that are particularly important in the catering industry.

Consumers follow a certain sequence of behaviors that are conditioned by various factors. Hie results obtained are related to the empirical context of the research.

More research is needed, along with variables and possibly other methods of analysis, to increase the effectiveness of these studies. Continuous research on consumer behavior, its changes, and dynamics allows for a better understanding of consumers, adapting to their expectations and needs, which in turn leads to increased sales and profits for the company.

Digital technologies open up new, previously unknown opportunities for gastronomy establishments. Thanks to them, it becomes possible to know and meet the needs of consumers. Analysis of large data sets has particular potential. For this purpose, guest reviews collected in aggregators of opinions about the companies: TripAdvisor, Google, Facebook, Pyszne, and Uber, also available to users in the form of mobile applications, are necessary. The mobile channel has become the main source of information about interests and preferences. Profiled data allow the implementation of an advertising campaign of the restaurant targeted at a very specific group of consumers interested in specific products or services.

Replication studies of clearly diverse consumer groups should be conducted, maintaining main research variables and including changing attitudes and motivations. It should also be mentioned that research restrictions relate to the empirical implementation of research and its consequences for the results.


Buchnowska, D. (2017). Systemy CRM w dobie konwergencji nowoczesnych technolo-gii informacyjnych [CRM systems in the era of convergence of modern information technologies], Zarzqdzanie i Finanse Journal of Management and Finance, 15(4), 225-226.

Connick, H. (2017). Turning Big Data into Big Insights. Retrieved from https://www.ama. org/marketing-news/turning-big-data-into-big-insights/.

Conway, D., Klabjan, D. (2013). Innovation Patterns of Big Data. In J. Liebowitz, Big Data and Business Analytics, Boca Raton, FL: CRC Press, Taylor & Francis Group, LLC, pp. 131-147.

Derek, M„ Duda-Gromada, K., Kosowska, P., Kowalczyk, A., Madurowicz, M. (2013). Problemowe i problematyczne ABC turystyki w Warszawie [Problem and problematic ABC of tourism in Warsaw], Prace Geograficzne, 134—140.

Doloitte. (2019). Technology, Media, and Telecommunications Predictions 2020. Retrieved from [accessed 20.11.2019].

Emplo. (2018). Retrieved from [accessed

20.11.2019] .

European Parliament. (2019). Retrieved from [accessed

2.12.2019] .

EY. (2015). Homo Informations: How Do Digital Consumers Behave Online! Retrieved from informaticus/$FILE/ey_homo_informaticus.pdf [accessed 2.12.2019].

Facebook. (2019). Retrieved from

GUS. (2016, 2017). Statistics Poland. Retrieved from [accessed


Horrigan, M. (2013). Big Data: A Perspective from the BLS, Amstat News, January 2013 Retrieved from

Kowalczuk, I. (2012). Zachowania konsumentow na rynku usluggastronomicznych [Consumer Behaviour on the Catering Market]. Warszawa, PL: Wydawnictwo SGGW.

Mobile Trends (2017). Retrieved from [accessed 10.12.2019].

Morgan, K., Sonnino, R. (2010). The urban foodscape: World cities and the new food equation. Cambridge Journal of Regions: Economy and Society, 3(2), 209-210.

Tabakow, M., Korczak, J., Franczyk, B. (2014). Big data - definicje, wyzwania i technologic informatyczne [Big-data-definitions, challenges, and information technologies]. Business Informatics, 7(31), 139-141.

Trajman, O. (2013). The intrinsic value of data, in big data and business analytics. In J. Liebowitz, (ed.), Boca Raton, FL: CRC Press, Taylor Si Francis Group.

Warsaw Tour. (2019). Retrieved from

Worldometers. (2019). Retrieved from

Wroblewska, W. (2013). Zarzadzanie relacjami z klientami jako zrodlo sukcesu organizacji [Customer relationship management (CRM) as a source of organization success], Zeszyty Naukowe Uniwersytetu Przyrodniczo — Humanistycznego w Siedlcach, 97, 229-239.

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