INNOVATIVE TOOLS OF MARKETING RESEARCH IN MARKETING COMMODITY AND COMMUNICATION POLICY OF TRADE ESTABLISHMENTS

Section "Economics": Economic and legal problems of sustainable development

Abstract

The article considers the directions of application of innovative tools of marketing research in the processes of formation of marketing commodity and communication policy of trade establishments. The options for companies to use artificial intelligence tools and in-depth site analysis in the marketing commodity and communication policy of FMCG market players are generalized. Prospects, advantages and problems of using Big Data Analysis as an innovation of marketing research in the field of retail are outlined. Areas of marketing innovations in FMCG are structured based on the application of big data. It is noted that the management of leading companies in the field of food retail should pay attention to the available budget information technologies Big Data and ensure their quality implementation in the system of marketing communications. The tasks that Big Data Analysis technology is able to solve in the processes of formation and implementation of marketing commodity and communication policy of local and regional retail chains, other retail business operators are identified. It has been proven that Big Data in itself does not give any competitive advantage and only its proper use can give the marketing of the retail network an understanding of how to act properly. Some data collection tools that are most effective in offline retail, online retail are considered. The directions of search of decisions on development of actions on overcoming of consequences of corona crisis by the analytical tools which can adjust a commodity and communication policy of trade establishments are defined.


REFERENCES
1. Syniavskyi M. Koronavirus vs biznes: yak Big Data dopomozhe ryteilu podolaty koronakryzu. Mind.ua. 16.04.2020. URL: https://mind.ua/openmind/20209726-koronavirus-vs-biznes-yak-big-data-dopomozhe-ritejlu-podolatikoronakrizu [in Ukrainian].
2. Sait mizhnarodnoi kompanii Boston Consulting Group. URL: https://www.bcg.com/ [in Ukrainian].
3. Rost cherez innovacii. Analiticheskij otchet. URL: https://ru.investinrussia.com/data/files/sectors/ru/inno-1.pdf [in Russian].
4. Gijom Sh., Dzheff G., De Bellefon N., Tejlor S., Vinsent L., Zhjul’en B., Dzhimmi R. Iskusstvennyj intellekt i uglublennaja analitika. Novye vozmozhnosti dlja rosta v sfere potrebitel’skih tovarov. BCG Review. 2019. No. 46. Aprel’. P. 35-43. URL: https://image-src.bcg.com/Images/BCG_Review_April-2019_tcm27-217213.pdf [in Russian].
5. Next Big Thing: Srez po global’nomu venchurnomu rynku i naibolee proryvnym tehnologijam, novym biznes modeljam. Strategy&. 2018. URL: https://www.strategyand.pwc.com/ru/ru/reports/2018/next-big-thing-q2.html [in Russian].
6. Arhangel’skaja S. Dejstvitel’no bol’shie dannye: kak big data pomogaet kompanijam zarabatyvat’. The Bell. 17.02.2020. URL: https://thebell.io/dejstvitelno-bolshie-dannye-kak-big-data-pomogaet-kompaniyam-zarabatyvat/ [in Russian].
7. Bol’shie dannye (Big Data). Tadviser: Gosudarstvo. Biznes. IT. 24.10.2017. URL: https://www.tadviser.ru/index.php/Stat’ja:Bol’shie_dannye_(Big_Data) [in Russian].
8. Manyika J., Chui M., Brown B., Bughin J., Dobbs R., Roxburgh C., and Hung Byers A. Big data: The next fron tier for innovation, competition, and productivity. McKinsey & Company. URL: https://www.mckinsey.com/businessfunctions/mckinsey-digital/our-insights/big-data-the-next-frontier-for-innovation#
9. Goad N., Robinson Dzh., Aviles S. Kak udovletvorit’ potrebnosti pokupatelej pri pomoshhi bol’shih dannyh. BCG Review. 2019. Aprel’. No. 46. P. 35-43. URL: https://image-src.bcg.com/Images/BCG_Review_April-2019_tcm27-217213.pdf [in Russian].
10. Sambudagva D.B. Big Data Analysis v sfere produktovogo ritejla. Biznes-obrazovanie v jekonomike znanij. 2015. No. 1. P. 113-114. URL: https://cyberleninka.ru/article/n/big-data-analysis-v-sfere-produktovogo-riteyla [in Russian].
11. Majer-Shenberger V., Kuk’er K. Bol’shie dannye. Revoljucija, kotoraja izmenit to, kak my zhivem, rabotaem i myslim. M. : Mann, Ivanov i Ferber, 2014. 240 p. [in Russian].
12. Tan P.-N. Introduction to Data Mining. Addison-Wesley Longman Publishing Co., Inc. Boston, MA, USA, 2005. 202 p.
13. Big Data v sovremennom ritejle: prediktivnye tehnologii dlja rosta Retention i LTV. 23.07.2020. URL: https://retailrocket.ru/blog/big-data-v-sovremennom-ritejle/ [in Russian].
14. Zahir M. Reklama dlja umnyh: kak retejl ispol’zuet tehnologii v bor’be za pokupatelja. Forbes. 14.02.2019. URL: https://www.forbes.ru/tehnologii/372373-reklama-dlya-umnyh-kak-reteyl-ispolzuet-tehnologii-v-borbe-zapokupatelya [in Russian].
15. More than just a [FirstName]. Real consumers share whatpersonalized experiences they expect. URL: https://us.epsilon.com/power-of-me
16. Baranov R. Analiz Big Data v ritejle: ot jeksperimentov k biznes-kejsam. URL: https://retail-loyalty.org/journal_retail_loyalty/read_online/art181701/ [in Russian].
17. Budnikevych I. Munitsypalnyi marketynh: teoriia, metodolohiia, praktyka: monohrafiia. Chernivtsi: Chernivetskyi natsionalnyi universytet. 2012. 645 p.

Keywords

marketing research, marketing innovations, marketing commodity policy, marketing communication policy, Big Data Analysis, artificial intelligence technologies, trade establishments, retail

Downloads

Download data is not yet available.

References

1. Синявський М. Коронавірус vs бізнес: як Big Data допоможе ритейлу подолати коронакризу. Mind.ua. 16.04.2020. URL: https://mind.ua/openmind/20209726-koronavirus-vs-biznes-yak-big-data-dopomozhe-ritejlupodolati-koronakrizu (дата звернення: 05.05.2020).

2. Сайт міжнародної компанії Boston Consulting Group. URL: https://www.bcg.com/ (дата звернення: 05.05.2020).

3. Рост через инновации. Аналитический отчет. URL: https://ru.investinrussia.com/data/files/sectors/ru/inno-1. pdf (дата обращения: 07.05.2020).

4. Гийом Ш., Джефф Г., Де Беллефон Н., Тейлор С., Винсент Л., Жюльен Б., Джимми Р. Искусственный интеллект и углубленная аналитика. Новые возможности для роста в сфере потребительских товаров. BCG Review. 2019. № 46. Апрель. С. 35—43. URL: https://image-src.bcg.com/Images/BCG_Review_April-2019_tcm27-217213.pdf (дата обращенияя: 07.05.2020).

5. Next Big Thing: Срез по глобальному венчурному рынку и наиболее прорывным технологиям, новым бизнес моделям. Strategy&. 2018. URL: https://www.strategyand.pwc.com/ru/ru/reports/2018/next-big-thing-q2.html (дата обращения: 29.04.2020).

6. Архангельская С. Действительно большие данные: как big data помогает компаниям зарабатывать. The Bell. 17.02.2020. URL: https://thebell.io/dejstvitelno-bolshie-dannye-kak-big-data-pomogaet-kompaniyamzarabatyvat/ (дата обращения: 29.04.2020).

7. Большие данные (Big Data). Tadviser: Государство. Бизнес. ИТ. 24.10.2017. URL: https://www.tadviser.ru/index.php/Статья:Большие_данные_(Big_Data) (дата обращения: 08.05.2020).

8. Manyika J., Chui M., Brown B., Bughin J., Dobbs R., Roxburgh C., and Hung Byers A. Big data: The next frontier for innovation, competition, and productivity. McKinsey & Company. URL: https://www.mckinsey.com/businessfunctions/mckinsey-digital/our-insights/big-data-the-next-frontier-for-innovation# (last accessed: 08.05.2020).

9. Гоад Н., Робинсон Дж., Авилес С. Как удовлетворить потребности покупателей при помощи больших данных. BCG Review. 2019. Апрель. № 46. С. 35—43. URL: https://image-src.bcg.com/Images/BCG_Review_April-2019_tcm27-217213.pdf (дата обращения: 08.05.2020).

10. Самбудагва Д.Б. Big Data Analysis в сфере продуктового ритейла. Бизнес-образование в экономике знаний. 2015. № 1. С. 113—114. URL: https://cyberleninka.ru/article/n/big-data-analysis-v-sfere-produktovogo-riteyla (дата обращения: 01.06.2020).

11. Майер-Шенбергер В., Кукьер К. Большие данные. Революция, которая изменит то, как мы живем, работаем и мыслим. Москва: Манн, Иванов и Фербер, 2014. 240 с.

12. Tan P.-N. Introduction to Data Mining. Addison-Wesley Longman Publishing Co., Inc. Boston, MA, USA, 2005. 202 p.

13. Big Data в современном ритейле: предиктивные технологии для роста Retention и LTV. 23.07.2020. URL: https://retailrocket.ru/blog/big-data-v-sovremennom-ritejle/ (дата обращения: 01.06.2020).

14. Захир М. Реклама для умных: как ретейл использует технологии в борьбе за покупателя. Forbes. 14.02.2019. URL: https://www.forbes.ru/tehnologii/372373-reklama-dlya-umnyh-kak-reteyl-ispolzuet-tehnologii-v-borbe-zapokupatelya (дата обращения: 01.06.2020).

15. More than just a [FirstName]. Real consumers share whatpersonalized experiences they expect. URL: https://us.epsilon.com/power-of-me (last accessed: 08.05.2020).

16. Баранов Р. Анализ Big Data в ритейле: от экспериментов к бизнес-кейсам. URL: https://retail-loyalty.org/journal_retail_loyalty/read_online/art181701/ (дата обращения: 01.06.2020).

17. Буднікевич І. Муніципальний маркетинг: теорія, методологія, практика. Чернівці: Чернівецький національний університет. 2012. 645 с.

Abstract views: 30
PDF Downloads: 6
Published
2020-08-25