Capability Maturity Model for data-driven marketing

Data-driven decision-making is gaining buzz and popularity across organizational functions and industries. Consequently, data analysis and marketing analytics enable companies of various size and business volume to leverage sustainable performance outcomes and continuous growth through data-driven m...

Full description

Bibliographic Details
Main Author: Länsipuro, Heidi
Other Authors: Jyväskylä University School of Business and Economics, Jyväskylän yliopiston kauppakorkeakoulu, Taloustieteet, Business and Economics, Jyväskylän yliopisto, University of Jyväskylä
Format: Master's thesis
Language:eng
Published: 2020
Subjects:
Online Access: https://jyx.jyu.fi/handle/123456789/68270
_version_ 1828193069305954304
author Länsipuro, Heidi
author2 Jyväskylä University School of Business and Economics Jyväskylän yliopiston kauppakorkeakoulu Taloustieteet Business and Economics Jyväskylän yliopisto University of Jyväskylä
author_facet Länsipuro, Heidi Jyväskylä University School of Business and Economics Jyväskylän yliopiston kauppakorkeakoulu Taloustieteet Business and Economics Jyväskylän yliopisto University of Jyväskylä Länsipuro, Heidi Jyväskylä University School of Business and Economics Jyväskylän yliopiston kauppakorkeakoulu Taloustieteet Business and Economics Jyväskylän yliopisto University of Jyväskylä
author_sort Länsipuro, Heidi
datasource_str_mv jyx
description Data-driven decision-making is gaining buzz and popularity across organizational functions and industries. Consequently, data analysis and marketing analytics enable companies of various size and business volume to leverage sustainable performance outcomes and continuous growth through data-driven marketing. Still, marketing professionals lack the tools, skillsets and procedures in turning this data into insights, and, furthermore, insights into action. Furthermore, research has yet not addressed these issues of data-driven marketing practice. Hence, this thesis aims to tackle a gap in current research and practice, and to gain further knowledge into the fragmented research on data-driven marketing. The goal of this study is to discover and understand the current level of data- driven decision-making as well as marketing analytics usage in marketing departments. Additionally, this thesis seeks to discover possible barriers that hinder such process development and usage of analytics for marketers. In doing so, this thesis aims to identify and create a model that describes the degree to which marketing analytical insights and data-driven methods are used in an organization and what may block the progression in this model for marketers.  This thesis takes a qualitative approach to the research dilemma. The data and methodology used in this research include ten marketing professionals’ interviews, as well as a thorough literature review to describe the theoretical framework and to position for this thesis. The data-driven marketing maturity and capability of each case organization was evaluated through qualitative analysis by reflecting the interviewees’ answers on the different levels of the Maturity Model. Through this, a Data-driven Marketing Capability Maturity Model was conceptualized. The thesis further extends the existing research on Capability Maturity Models by introducing barriers to data-driven marketing. These barriers were classified into three different categories: organizational structure barriers, organizational culture barriers and top management barriers. The barriers were placed onto the Data-driven Marketing Capability Maturity Model, to identify the major obstacles to moving forward in each level.
first_indexed 2020-03-23T21:01:00Z
format Pro gradu
free_online_boolean 1
fullrecord [{"key": "dc.contributor.advisor", "value": "Karjaluoto, Heikki", "language": "", "element": "contributor", "qualifier": "advisor", "schema": "dc"}, {"key": "dc.contributor.advisor", "value": "Shaikh, Aijaz A.", "language": "", "element": "contributor", "qualifier": "advisor", "schema": "dc"}, {"key": "dc.contributor.author", "value": "L\u00e4nsipuro, Heidi", "language": "", "element": "contributor", "qualifier": "author", "schema": "dc"}, {"key": "dc.date.accessioned", "value": "2020-03-23T08:17:47Z", "language": null, "element": "date", "qualifier": "accessioned", "schema": "dc"}, {"key": "dc.date.available", "value": "2020-03-23T08:17:47Z", "language": null, "element": "date", "qualifier": "available", "schema": "dc"}, {"key": "dc.date.issued", "value": "2020", "language": "", "element": "date", "qualifier": "issued", "schema": "dc"}, {"key": "dc.identifier.uri", "value": "https://jyx.jyu.fi/handle/123456789/68270", "language": null, "element": "identifier", "qualifier": "uri", "schema": "dc"}, {"key": "dc.description.abstract", "value": "Data-driven decision-making is gaining buzz and popularity across organizational\nfunctions and industries. Consequently, data analysis and marketing analytics enable\ncompanies of various size and business volume to leverage sustainable performance\noutcomes and continuous growth through data-driven marketing. Still, marketing\nprofessionals lack the tools, skillsets and procedures in turning this data into insights,\nand, furthermore, insights into action. Furthermore, research has yet not addressed\nthese issues of data-driven marketing practice. Hence, this thesis aims to tackle a gap in\ncurrent research and practice, and to gain further knowledge into the fragmented\nresearch on data-driven marketing.\nThe goal of this study is to discover and understand the current level of data-\ndriven decision-making as well as marketing analytics usage in marketing departments.\nAdditionally, this thesis seeks to discover possible barriers that hinder such process\ndevelopment and usage of analytics for marketers. In doing so, this thesis aims to\nidentify and create a model that describes the degree to which marketing analytical\ninsights and data-driven methods are used in an organization and what may block the\nprogression in this model for marketers.\u00a0\nThis thesis takes a qualitative approach to the research dilemma. The data and\nmethodology used in this research include ten marketing professionals\u2019 interviews, as\nwell as a thorough literature review to describe the theoretical framework and to position\nfor this thesis. The data-driven marketing maturity and capability of each case\norganization was evaluated through qualitative analysis by reflecting the interviewees\u2019\nanswers on the different levels of the Maturity Model. Through this, a Data-driven\nMarketing Capability Maturity Model was conceptualized. The thesis further extends the\nexisting research on Capability Maturity Models by introducing barriers to data-driven\nmarketing. These barriers were classified into three different categories: organizational\nstructure barriers, organizational culture barriers and top management barriers. The\nbarriers were placed onto the Data-driven Marketing Capability Maturity Model, to\nidentify the major obstacles to moving forward in each level.", "language": "en", "element": "description", "qualifier": "abstract", "schema": "dc"}, {"key": "dc.description.provenance", "value": "Submitted by Miia Hakanen (mihakane@jyu.fi) on 2020-03-23T08:17:47Z\nNo. of bitstreams: 0", "language": "en", "element": "description", "qualifier": "provenance", "schema": "dc"}, {"key": "dc.description.provenance", "value": "Made available in DSpace on 2020-03-23T08:17:47Z (GMT). No. of bitstreams: 0\n Previous issue date: 2020", "language": "en", "element": "description", "qualifier": "provenance", "schema": "dc"}, {"key": "dc.format.extent", "value": "76", "language": "", "element": "format", "qualifier": "extent", "schema": "dc"}, {"key": "dc.format.mimetype", "value": "application/pdf", "language": null, "element": "format", "qualifier": "mimetype", "schema": "dc"}, {"key": "dc.language.iso", "value": "eng", "language": null, "element": "language", "qualifier": "iso", "schema": "dc"}, {"key": "dc.rights", "value": "In Copyright", "language": "en", "element": "rights", "qualifier": null, "schema": "dc"}, {"key": "dc.subject.other", "value": "marketing analytics", "language": "", "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.subject.other", "value": "data-driven marketing", "language": "", "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.subject.other", "value": "marketing measurement", "language": "", "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.subject.other", "value": "data-driven decision-making", "language": "", "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.subject.other", "value": "Capability Maturity Model", "language": "", "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.title", "value": "Capability Maturity Model for data-driven marketing", "language": "", "element": "title", "qualifier": null, "schema": "dc"}, {"key": "dc.type", "value": "master thesis", "language": null, "element": "type", "qualifier": null, "schema": "dc"}, {"key": "dc.identifier.urn", "value": "URN:NBN:fi:jyu-202003232498", "language": "", "element": "identifier", "qualifier": "urn", "schema": "dc"}, {"key": "dc.type.ontasot", "value": "Pro gradu -tutkielma", "language": "fi", "element": "type", "qualifier": "ontasot", "schema": "dc"}, {"key": "dc.type.ontasot", "value": "Master\u2019s thesis", "language": "en", "element": "type", "qualifier": "ontasot", "schema": "dc"}, {"key": "dc.contributor.faculty", "value": "Jyv\u00e4skyl\u00e4 University School of Business and Economics", "language": "en", "element": "contributor", "qualifier": "faculty", "schema": "dc"}, {"key": "dc.contributor.faculty", "value": "Jyv\u00e4skyl\u00e4n yliopiston kauppakorkeakoulu", "language": "fi", "element": "contributor", "qualifier": "faculty", "schema": "dc"}, {"key": "dc.contributor.department", "value": "Taloustieteet", "language": "fi", "element": "contributor", "qualifier": "department", "schema": "dc"}, {"key": "dc.contributor.department", "value": "Business and Economics", "language": "en", "element": "contributor", "qualifier": "department", "schema": "dc"}, {"key": "dc.contributor.organization", "value": "Jyv\u00e4skyl\u00e4n yliopisto", "language": "fi", "element": "contributor", "qualifier": "organization", "schema": "dc"}, {"key": "dc.contributor.organization", "value": "University of Jyv\u00e4skyl\u00e4", "language": "en", "element": "contributor", "qualifier": "organization", "schema": "dc"}, {"key": "dc.subject.discipline", "value": "Markkinointi", "language": "fi", "element": "subject", "qualifier": "discipline", "schema": "dc"}, {"key": "dc.subject.discipline", "value": "Marketing", "language": "en", "element": "subject", "qualifier": "discipline", "schema": "dc"}, {"key": "yvv.contractresearch.funding", "value": "0", "language": "", "element": "contractresearch", "qualifier": "funding", "schema": "yvv"}, {"key": "dc.type.coar", "value": "http://purl.org/coar/resource_type/c_bdcc", "language": null, "element": "type", "qualifier": "coar", "schema": "dc"}, {"key": "dc.rights.accesslevel", "value": "openAccess", "language": null, "element": "rights", "qualifier": "accesslevel", "schema": "dc"}, {"key": "dc.type.publication", "value": "masterThesis", "language": null, "element": "type", "qualifier": "publication", "schema": "dc"}, {"key": "dc.subject.oppiainekoodi", "value": "20423", "language": "", "element": "subject", "qualifier": "oppiainekoodi", "schema": "dc"}, {"key": "dc.subject.yso", "value": "markkinointi", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.subject.yso", "value": "tiedonhallinta", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.subject.yso", "value": "digitaalinen markkinointi", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.subject.yso", "value": "tiet\u00e4myksenhallinta", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.subject.yso", "value": "data", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.subject.yso", "value": "marketing", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.subject.yso", "value": "information management", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.subject.yso", "value": "digital marketing", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.subject.yso", "value": "knowledge management", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.subject.yso", "value": "data", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.format.content", "value": "fulltext", "language": null, "element": "format", "qualifier": "content", "schema": "dc"}, {"key": "dc.rights.url", "value": "https://rightsstatements.org/page/InC/1.0/", "language": null, "element": "rights", "qualifier": "url", "schema": "dc"}, {"key": "dc.type.okm", "value": "G2", "language": null, "element": "type", "qualifier": "okm", "schema": "dc"}]
id jyx.123456789_68270
language eng
last_indexed 2025-03-31T20:00:50Z
main_date 2020-01-01T00:00:00Z
main_date_str 2020
online_boolean 1
online_urls_str_mv {"url":"https:\/\/jyx.jyu.fi\/bitstreams\/d1b01e49-0971-443b-9907-7dd18052cf82\/download","text":"URN:NBN:fi:jyu-202003232498.pdf","source":"jyx","mediaType":"application\/pdf"}
publishDate 2020
record_format qdc
source_str_mv jyx
spellingShingle Länsipuro, Heidi Capability Maturity Model for data-driven marketing marketing analytics data-driven marketing marketing measurement data-driven decision-making Capability Maturity Model Markkinointi Marketing 20423 markkinointi tiedonhallinta digitaalinen markkinointi tietämyksenhallinta data marketing information management digital marketing knowledge management
title Capability Maturity Model for data-driven marketing
title_full Capability Maturity Model for data-driven marketing
title_fullStr Capability Maturity Model for data-driven marketing Capability Maturity Model for data-driven marketing
title_full_unstemmed Capability Maturity Model for data-driven marketing Capability Maturity Model for data-driven marketing
title_short Capability Maturity Model for data-driven marketing
title_sort capability maturity model for data driven marketing
title_txtP Capability Maturity Model for data-driven marketing
topic marketing analytics data-driven marketing marketing measurement data-driven decision-making Capability Maturity Model Markkinointi Marketing 20423 markkinointi tiedonhallinta digitaalinen markkinointi tietämyksenhallinta data marketing information management digital marketing knowledge management
topic_facet 20423 Capability Maturity Model Marketing Markkinointi data data-driven decision-making data-driven marketing digitaalinen markkinointi digital marketing information management knowledge management marketing marketing analytics marketing measurement markkinointi tiedonhallinta tietämyksenhallinta
url https://jyx.jyu.fi/handle/123456789/68270 http://www.urn.fi/URN:NBN:fi:jyu-202003232498
work_keys_str_mv AT länsipuroheidi capabilitymaturitymodelfordatadrivenmarketing