Digital analytics allows website owners to comprehend how their websites are used

DIGITAL ANALYTICS

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Executive SummaryDigital analytics allows website owners to comprehend how their websites are used, hence using the data to optimise customer experience on these websites while optimising their content offerings and marketing return on investment for business performance enhancement. The current report analyses digital analytics concepts as they apply to the Coventry Transport Museum’s website. The report is divided into three sections. The first is a literature review section that includes definitions of important terms, a discussion of different digital analytics concepts, and exploration of the role of digital analytics and websites in the development of a digital marketing strategy. The second section involves using digital analytics tools, digital marketing software, and digital marketing theories such as CRM to analyse and assess the Coventry Transport Museum’s website. The last section covers some recommendations for Coventry Transport Museum regarding bettering its digital strategy with a focus on its website.

Table of Contents

TOC o “1-3” h z u HYPERLINK l “_Toc33521261” Executive Summary PAGEREF _Toc33521261 h 2

HYPERLINK l “_Toc33521262” 1.0 Introduction PAGEREF _Toc33521262 h 3

HYPERLINK l “_Toc33521263” 2.0 Literature Review PAGEREF _Toc33521263 h 4

HYPERLINK l “_Toc33521264” 2.1 Definitions PAGEREF _Toc33521264 h 4

HYPERLINK l “_Toc33521265” 2.2 Key Themes PAGEREF _Toc33521265 h 5

HYPERLINK l “_Toc33521266” 2.2.1 Big Data Analytics PAGEREF _Toc33521266 h 5

HYPERLINK l “_Toc33521267” 2.2.2 Data Mining PAGEREF _Toc33521267 h 6

HYPERLINK l “_Toc33521268” 2.2.3 Data Visualisation PAGEREF _Toc33521268 h 6

HYPERLINK l “_Toc33521269” 2.2.4 Web Analytics and Clickstreams PAGEREF _Toc33521269 h 6

HYPERLINK l “_Toc33521270” 2.3 Role of Digital Analytics and Websites in Digital Marketing Strategy Development PAGEREF _Toc33521270 h 7

HYPERLINK l “_Toc33521271” 3.0 Analysis of Coventry Transport Museum Website PAGEREF _Toc33521271 h 7

HYPERLINK l “_Toc33521272” 3.1 General Analysis PAGEREF _Toc33521272 h 8

HYPERLINK l “_Toc33521273” 3.2 Qualitative Analysis PAGEREF _Toc33521273 h 8

HYPERLINK l “_Toc33521274” 3.3 Quantitative Analysis PAGEREF _Toc33521274 h 9

HYPERLINK l “_Toc33521275” 3.3.1 MOZBar PAGEREF _Toc33521275 h 9

HYPERLINK l “_Toc33521276” 3.3.2 SEOquake PAGEREF _Toc33521276 h 9

HYPERLINK l “_Toc33521277” 3.3.3 SEMRush Stats PAGEREF _Toc33521277 h 9

HYPERLINK l “_Toc33521278” 3.3.4 Web Traffic Displayer PAGEREF _Toc33521278 h 10

HYPERLINK l “_Toc33521279” 3.3.5 WooRank PAGEREF _Toc33521279 h 10

HYPERLINK l “_Toc33521280” 3.4 Marketing Theory and Frameworks PAGEREF _Toc33521280 h 10

HYPERLINK l “_Toc33521281” 4.0 Recommendations PAGEREF _Toc33521281 h 11

HYPERLINK l “_Toc33521282” Reference List PAGEREF _Toc33521282 h 13

HYPERLINK l “_Toc33521283” Appendices PAGEREF _Toc33521283 h 16

1.0 IntroductionIn the contemporary marketing world, key marketing decisions no longer rely on past experience and hypothetical predispositions. Rather, these decisions are driven and guided by analytics and Big Data, which are instrumental in generating influential marketing ideas and insights. Specifically, predictive data analytics enables enterprises to properly determine their return on investments while attaining tactical and strategic insights that culminate in ongoing business improvement, effective business strategies, and sound organisational decisions across departments and teams (Järvinen 2016; Lee et al 2001). Essentially, digital analytics offer businesses with rich data and insights into improving the performance of their websites, along with comprehending how their marketing campaigns influence conversion rates and customers’ journeys. Given this statement, the current report examines the application of digital analytics concepts in the Coventry Transport Museum’s context. Particularly, it includes a literature review on digital analytics and its role in digital marketing strategy development. Further, the essay analyses and evaluates the Coventry Transport Museum’s website using different digital analytics tools and digital marketing theories before offering recommendations for the institution to improve its digital strategy in connection with its website.

2.0 Literature Review2.1 DefinitionsRansbotham, Kiron, and Prentice (2015) define analytics as the process of using data and the associated business insights to guide and steer fact-based decisions, planning, execution, learning, measurement, and management within enterprises. These data and insights are created via applied analytical disciplines, techniques, and models such as contextual, cognitive, predictive, quantitative, and statistical models (Power et al. 2018; Ransbotham et al. 2015). So, analytics enables the discovery, interpretation, synthesis, and communication of meaningful data patterns, together with the applications of these patterns to drive effective decision making. Based on this definition, digital analytics is the process of analysing quantitative and qualitative data from businesses and their competition to drive incessant improvement of the online experiences for both clients and potential clients, translating in desired offline and online outcomes (Kaushik 2010).

2.2 Key ThemesDigital analytics relate to other key concepts that include Big Data analytics, data mining, data visualisation, web analytics, and clickstream.

2.2.1 Big Data AnalyticsDifferent researchers have examined the concept of Big Data analytics and the consensus among most of them is that it entails the identification, analysis, aggregation, manipulation, synthesis, management, and storage of relevant data to improve decision-making capabilities (Raghupathi and Raghupathi 2014; Sivarajah et al. 2017). Big Data analytics also enables institutions to address the challenge of locating and obtaining information in real-time when different data sets are dispersed across numerous unlinked data systems (Daniel 2015). Big Data analytics is part of digital analytics that plays a critical role in customer relationship management, market research, digital marketing, data visualisation, and client engagement (Harrison and Bukstein 2016). Also, Big Data analytics is instrumental to quality management, profitability augmentation, and cost reductions while minimising performance variability (Elgendy and Elragal 2014; Kolajo, Daramola, and Adebiyi 2019). Essentially, implementing a systematic, Big-Data-centred analytics strategy generates a sustainable competitive advantage.

2.2.2 Data MiningIn digital analytics, data mining encompasses the processes and techniques employed in deeper data exploration aiming at extracting value and relevant inferences from data sets to enable more accurate and strategic decisions (Power et al. 2018). The availability of digital analytics solutions and applications such as Google Analytics, AT Internet’s Analytics Suite, and social media analytics simplify data mining processes. Besides these digital analytics tools, other algorithms and methods employed in data mining include classification, association rule generation, frequent pattern mining, sequential pattern generation, and clustering (Benhlima 2018). These methods facilitate rapid extractions of the most relevant data and information without necessarily engaging computational efforts. Lee et al (2001) acknowledge that data mining techniques can be used in modelling websites in electronic commerce set-ups. In digital analytics, data must first be cleaned, transformed, and classified before being made available for data mining and other digital analytical functions. What this means is that data mining only deals with structured data, not unstructured and semi-structured data (Elgendy and Elragal 2014).

2.2.3 Data VisualisationIn digital analytics, data visualisation refers to the presentation of data points using pie, bar, and line charts, diagrams, maps, graphs, and pictures (Elgendy and Elragal 2014; Hanamanthrao and Thejaswini 2017). Data visualisation is essential in perceiving and comprehending data patterns and trends.

2.2.4 Web Analytics and ClickstreamsWeb analytics is a component of digital analytics that deals with collecting, measuring, analysing, and reporting web-based data aiming at comprehending and optimising website usage (Järvinen 2016; Kaushik 2010). Clickstreams are a tracking technique used as part of web analytics in recording user activities on websites to aid digital marketing research (Hanamanthrao and Thejaswini 2017; Kateja et al. 2014).

2.3 Role of Digital Analytics and Websites in Digital Marketing Strategy DevelopmentWhen Convert Transport Museum wants to develop its digital marketing strategy, digital analytics and its website play a key role. Digital analytics provides digital intelligence needed in comprehending how customers use the firm’s website, informing decisions that go into the organisation’s digital marketing strategy. Digital intelligence includes accurate data about audiences, channels, customer website-usage behaviours, key result areas, key performance indicators, and websites’ digital metrics (Power et al. 2018; Raghupathi and Raghupathi 2014). Also, digital analytics is necessary for examining both qualitative and quantitative digital data and measuring outcomes associated with this data to determine the aspects of continual improvement and website optimisation campaigns to include in the digital marketing strategy. Also, digital analytics allows businesses to test their objectives in determining whether the objectives align with customers’ needs, which provides insights into the digital marketing strategy. Furthermore, a blend of digital marketing analytics and web analytics translates customer behaviour into actionable business facts and provide a creative and fluid data-driven groundwork for building a profitable and scalable marketing strategy (Hudson 2019). Lastly, digital analytics provides two solutions, namely, social media monitoring (SMM) software and Web analytics (WA) used in measuring and improving digital marketing performance, thereby yielding data that is indispensable in digital marketing strategy design.

3.0 Analysis of Coventry Transport Museum Website3.1 General Analysis

The design of the Coventry Transport Museum’s website ( HYPERLINK “https://www.transport-museum.com/” https://www.transport-museum.com/) is appealing as it highlights the key information that the institution wishes to convey to the target online audiences. It includes information about the website designer (LightMedia), institutional partners, accessible quick links and popup links to additional information about the Museum, and the institution’s registration information. Other details captured in this website include cookie and privacy policies, links to social media (Twitter and Facebook), the Museum’s location, and a search icon that enables target online audiences to search specific themes relating to this institution.

3.2 Qualitative AnalysisCoventry Transport Museum’s website incorporates visual content into textual content. The visual content appears as images with enlightening text, infographics of ticket admissions and other items, the organisation’s logo, and signature branded images of partner firms such as European Union, Heritage Lottery, and Arts Council of England, among others. From the infographics, some service offerings of this Museum are identifiable, which include interactive exhibitions for schools, collections of outstanding feats of British engineering, and travel events. Furthermore, the website’s content reveals the institution’s working hours. The opening hours are between 10am and 5pm daily, from January 01 to December 31 except Christmas holiday when the Museum remains closed between December 24 and 26.

The website’s content design also makes it possible to deduce the Coventry Transport Museum’s goals. These goals include excellence in artistic and cultural experience, inclusiveness for everyone, ensuring children and young people experience the richness of the museum’s art, and educating and inspiring visitors through history. Furthermore, the website has clickable buttons and icons available to help in navigating the visual content. Besides these buttons and icons, it has a user-friendly navigation system that allows audiences to access and navigate through the information needed quickly and easily.

3.3 Quantitative AnalysisFive digital analytics tools, namely, MOZBar, SEMRush Stats, SEOquake, Woorank, and Web Traffic Displayer formed the basis for the quantitative analysis of the Museum’s website.

3.3.1 MOZBarThis analysis tool allowed for the instant generation of metrics on exposure metrics, page overlay, and page elements of the Coventry Transport Museum’s website. Based on the outcomes, this website has a page authority rating of 49 and a domain authority rating of 53 (See Appendix 1a). Compared to websites of other museums in Coventry (Coventry Watch Museum and Coventry Music Museum), this website has higher rankings as the page authority ratings of these two museums are 36 and 23 and their domain authority ratings are 31 and 35 respectively (See Appendix 1c).

3.3.2 SEOquakeThis tool showed the page rank, Alexa rank, backlinks, and keyword density of the Coventry Transport Museum’s website. This website has a higher page rank on SEMRush (1.05M) than on Bing (12. 3K) and Google (1.07K) (See Appendix 2).

3.3.3 SEMRush StatsThis digital analysis tool generated data about the backlink profile of the Museum’s website. Based on the data generated, the website has 5.8M backlink votes, 62.4 referral domains, and 61.7 referring IPs across five countries led by the U.S. (See Appendix 3).

3.3.4 Web Traffic DisplayerThis tool generated digital data about the traffic, advertising stack, and visitors of the Coventry Transport Museum’s website. Based on this tool, the estimated summary traffic is 613 sessions per day, 18.4 thousand sessions per month, and 6.72 million sessions annually.

3.3.5 WooRankThis digital analysis tool generates metrics relating to the Internet marketing effectiveness of the Coventry Transport Museum’s website up to February 2020. As per this tool that generates a dynamic grade out of a 100-point scale, this website has as a score of 52 points (See Appendix 5).

3.4 Marketing Theory and FrameworksThe marketing theories and frameworks relating to the analysis of the Coventry Transport Museum’s website include the consumer decision-making process (See Appendix 6), customer relationship management (CRM), and customer value creation. The consumer decision-making framework involves five steps: problem recognition, information search, alternatives’ evaluation, purchasing, and post-purchasing satisfaction (Professional Academy 2020). In the framework’s second step, search engines, websites such as that of the Coventry Transport Museum, and other digital marketing tools make information search easy. Regarding CRM, this website and other digital analytics tools are employed in analysing customer history and interactions with the institution towards improving business relationships with them and customising and personalising services to ensure retention (Anshari et al. 2018; Soliman 2011). Lastly, the customer value creation theory applies to this analysis in that the content and promotion messages on the Coventry Transport Museum’s website should be customised to create exceptional customer experiences that add value to visiting audiences (Dhangal 2020).

4.0 RecommendationsCoventry Transport Museum can improve its digital strategy through the enrichment of its website by adopting and implementing four recommendations. The first recommendation entails pursuing referral traffic to augment the website’s Internet marketing effectiveness. The data generated using WooRank made it evident that the online marketing effectiveness of this website is just above average with a score of 52 points. Leveraging referral traffic would help create and display valuable and enriched content that attracts audiences of people and institutions to link to it rather than persuading other sites to link back to this website (SEO.co 2020). This would increase traffic, efficiently boosting the online marketing effectiveness score to higher values.

The second recommendation is the implementation of search engine optimisation microdata. SEO microdata refers to a code language the design of which provides search engine programs with information about web content (Kumar 2012). When conducting the quantitative analysis of the Coventry Transport Museum’s website, it was not recognised by analytics tools such as SimilarWeb, Alexa Toolbar, VStat, and Open SEO Stats, among others. So, the rationale for this recommendation is to enable its recognition by such tools by making it easier for search engines to crawl for the website. Also, microdata would create rich snippets that display more data on search results webpages than it would be achieved through traditional listings (Kumar 2012). This would improve the indexing and ranking of this website, eventually enhancing its digital strategy.

The third recommendation is to improve efforts in leveraging social media marketing. The analysis established that the Coventry Transport Museum’s website links only to two social media (Facebook and Twitter). Contemporary digital marketing is characterised by a broad gamut of other social media besides these two, including Instagram, Reddit, Pinterest, Google+, and others that can be useful digital marketing tools. This institution needs to understand the need to be proactive because producing great content is one thing and getting people to find this content is another. So, it should customise its website to include links to more social media channels that offer personalised search results and allow traction, thereby promoting its content adequately to increase traffic (Järvinen 2016).

The last recommendation is to increase its focus on on-page search engine optimisation. On-page optimisation of the content for search engines supported by the Coventry Transport Museum’s website would involve creating additional internal links, speed-oriented Meta descriptions, and image SEO alt tags that boost the website’s organic traffic.

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Elgendy, N., and Elragal, A. (2014) Big data analytics: a literature review paper. In Industrial Conference on Data Mining (pp. 214-227). Springer, Cham.

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AppendicesAppendix 1: Quantitative Analysis of the Museum Using MOZBar

Overview

Ranking Distribution

Comparative Domain (Overview)

Comparative Domain (Ranking Distribution)

Appendix 2: Quantitative Analysis of the Museum Using SEOquake

Appendix 3: Quantitative Analysis of the Museum Using SEMRush

Appendix 4: Quantitative Analysis of the Museum Using Web Traffic Displayer

Appendix 2: Quantitative Analysis of the Museum Using WooRank

Appendix 6: Consumer decision-making Process framework (Adapted from Professional Academy (2020))