52995/52996 Digital Marketing Analytics & Strategy Assignment Sample 2024
Introduction
Google products deal above all with different pieces, ranging from clothing to luggage, beverages and luggage, etc. sites all these items are available. Google is considered a multinational trading company worldwide. Investment online analysis, advertising technology, including desktop applications, was added to the Google product shop.
The business is now investing in the online market segment which offers different types of retail products available online in the market for goods. Google is now working together on a search engine testing initiative and job. Google provides apps and gadgets, such as pixels for Google, stadium nest products, headphones, call boxes, loaders, and keyboards, on the other side. In cooperation with several businesses, Google offers goods manufactured from countries around the world (Albright, 2020).
Aim of the study
Google stores general market offers retail items worldwide. This provides the customer with a unique one-click-button for every product on a single platform. Google’s commodity stores set market goals for the provision for the sale of multiple widely available goods for customers to greatly enhance their individual lives.
Objectives of the study
- To quantify user involvement inside online pages of the business at the same site of web viability.
- to acknowledge the involvement of a client community in the countries that access websites
- to reducing the bounce rate
Engagement of consumer
According to Bennet (2017) in a market, whether offline or online, consumer involvement plays a crucial role. Consumer involvement In digital marketing the involvement of consumers is defined as a business or marketing strategy following customer interactions providing personal texts or customer information on the channel. The most powerful primary digital marketing equipment is customer attraction to Google goods.
Content advertisement archives are saturated. These numbers help satisfy customer engagement with the increasing demand for the consumer. The employer has conserved -manner for its clients. The department contacts and retains the group across a wide range of means including e-mails, social communication, non-public communications, and community forums. The employer implemented a computer that you know to expect the destiny action of customers by showing the goods endorsed. It also enriches the dialogue by providing resources and goods by itself. That is why customer service participation is crucial for helping customers to upgrade the new interactions of a business, which is an important contact content.
Frequencies
As stated by Bolt (2020) consumer frequencies determine how shoppers are visiting the shop, how they look at goods shops, how many people are visiting the shop, and how long they spending in the shop. Customer contact frequency analysis ensures that consumers are constant in a business. The main web analysis, however, is often useful for frequency analysis.
the instrument for assessing and monitoring the effect of the website. This is measuring customer traffic in online shops. The web monitoring mechanism only serves the organization’s monitoring scheme. Web management framework estimates the results of specific advertisement promotions (Amiri et al., 2019).
Frequency: It encourages the recording of traffic-time systems on internet pages with a new promotion campaign. Statistics and several other consumers who visited the site were used in the website management scheme. The frequency permits traveler traffic to be detected and estimates the popularity trends of such customers, which cause costs to be included in the market view. The frequencies will determine the broad range of traffic on the websites in a given period. Defining the large range of visitors to the site or the timeframe to an average number of visitors to the site for any time (Bonini, (2019).
The period is one month or twelve months. A collection of capacity values was provided for frequency distribution and a quick record of statistics was provided. It provided the occurrence in the collection of statistical facts (Burgess, 2020). Alternatively, the information sequence is represented using the frequency range found in. It is the most common way of looking at the business characteristics in online worried variables. Frequencies estimate the broad range of customer visits.
Cross tabulation
The cross-table with columns and ranks allows vendors to have an eye on two or three factors. Cross-tablet splits uncooked data into subgroups and shows dependent changes in the component. In marketing studies, cross-tabulation is also the most used data collection technology. Clear data needed for a cross-table, as it also lets the analyst understand variables and elements inside the table. The method of Cross-tabletting diagrams details that help industry investigators gain a better business strategy and support the company.
The cross-table encourages the market analyst to establish a physically strong connection between market analysis and market behavior (Tesavrita et al., 2017). The market analyst can predict potential processes that demand analysis with the aid of cross-tabulations. Cross tabulation is used to describe the organization’s partnership management. Cross Tabulation is primarily done on categorical data that can be divided into similarly exclusive data. The company’s interpretation of the raw data from the industry will be challenging.
To view these data through tabulation data to help the analyst get a better understanding of the business conditions. In the goods of Google, the researcher must gather demand data to provide the business with a positive outcome for improved results, so that the company can easily achieve a good profit margin (Chaffey, 2019).
Regression Analysis
Google Goods uses a regression analysis approach to determine the modifications to the autonomous variables that affect the needy. The dependent variable is always revenue for a digital marketing company. The regression analysis model allows the company owner to measure the revenue crash for each sovereign component. A regression analysis model can help forecast a digital marketing percentage rise and help to increase revenue. The model of regression analysis will provide the idea of an increase and a decrease in revenue (Lawrence, 2019).
| Correlations | |||
| Users | New Users | ||
| Pearson Correlation | Users | 1.000 | 1.000 |
| New Users | 1.000 | 1.000 | |
| Sig. (1-tailed) | Users | . | .000 |
| New Users | .000 | . | |
| N | Users | 10 | 10 |
| New Users | 10 | 10 | |
| Model Summary | ||||
| Model | R | R Square | Adjusted R Square | Std. The error of the Estimate |
| 1 | 1.000a | 1.000 | 1.000 | 231.010 |
| a. Predictors: (Constant), New Users | ||||
| b. Dependent Variable: Users | ||||
| Coefficients | ||||||
| Model | Unstandardized Coefficients | Standardized Coefficients | t | Sig. | ||
| B | Std. Error | Beta | ||||
| 1 | (Constant) | -90.772 | 79.953 | -1.135 | .289 | |
| New Users | 1.094 | .006 | 1.000 | 176.334 | .000 | |
| a. Dependent Variable: Users | ||||||
To construct a regression analysis model, the scientist must remember a few points:
Choose always the correct question: the researcher wants to consider the dilemma the organization tries to fix before evaluating something. Data gathering: In the second phase, the analysis would gather data to help the investigator measure revenue in the business in one year. Interpret the analysis: it should provide a straightforward conclusion when analyzing results.
If the regression analysis produces a better outcome it makes sense, but if it does not yield a better result that will show that the study has not been done and the sales must be increased and that the other department must be focused. The study of regression is to assess the deficiency over the year. The research is designed to assess the requirements and reveal the deficiency.
Regression analysis includes data used to estimate the association between dependent variables and independent variables. The study of regression involves patterns such as linear, multiple, and non-linear variants. Simple liners are most often used in digital marketing and are the most popular model (Bullock, 2020).
Identification of consumer’s group
In this identity of the user, the supporting mechanism that can be handled by indirect customers is often the client of external processes that can supply information to domestic staff. The organization and the individuals who were impacted by the decision and who would influence their organization directly. In the group of customers, they know still who determines who will sell every commodity.
They are often connected to the indirect consumer to decide their motivating mechanism and to watch what is happening in the industry. Three consumer forms are always existing, future and current. There are always customers of three kinds. The current client has simple contact: it handles the key business database, a new client is an effective manner in which communication understands the needs of the consumer and former clients are the main points of reference to a customer which is preventing the customer’s frustration.
Frequencies
This rate applies to the amount and time of consumers who see the goods. Anyone who has seen your ad three times every 24 hours will see several targeted members. That’s three times the frequency. In the case of testing, the frequency of the results would be high and poor, causing the champion who began to sell goods difficulty. A new client is really difficult to enter in this kind of marketing. The key technique is to demonstrate the highest number of people in a couple of minutes.
The main reason is that brand awareness is simplified and new customers are made aware of their brand. The frequency phase of the massage does not depend on the stage below. This is the kind of food the consumer loves and would like to shop so that the customer is waiting for the brand to massage it. In terms of the low and higher frequency, it has a good picture of the branding company’s budget condition.
The world leads the most programmatic material of any advertisement, and it draws the viewer. prospective customers should be optimum. The main media claims there must be a timetable for delivering a letter which must be seen at least three times. The traditional is not correct in the original, either. The brand is the research and it is still a modern technology with the approach to work at the heart of the commodity that has industry expertise.
Variance Analysis
Variance analysis (ANOVA) is a statistical analytical technique that distributes the variable contained in data and is divided by random variables and systemic factors in bits. Factors grouped in a structured way affect statistically the data, which is not determined by random factors (Wen and Siqin, 2020).
| ANOVA | ||||||
| Model | Sum of Squares | df | Mean Square | F | Sig. | |
| 1 | Regression | 1659344569.503 | 1 | 1659344569.503 | 31093.775 | .000b |
| Residual | 426926.497 | 8 | 53365.812 | |||
| Total | 1659771496.000 | 9 | ||||
| a. Dependent Variable: Users | ||||||
| b. Predictors: (Constant), New Users | ||||||
The formula that ANOVA uses:
F= MST/ MSE
Where:
F= ANOVA coefficient, MST= mean sum of square due to trade, MSE= mean sum of square due to mistake.
ANOVA, the variance analysis shows the first step in analyzing errors that influence the data in question. After the research is over, the considerations dealing with methodology factors that are measured ably lead to uncertainty in the tests or the analysis performances. The ANOVA test used by the goggle researcher aims to disinfluencing the independent variable with the variable reliable for the regression analysis.
T- TEST
A t-test is a kind of inferential statistic to decide whether the mean differences in two classes are meaningful, and in some functions might be associated. It is mostly used in the event of a regular distribution, including the data collection reported as a result of the rejection of a coin 100 times, and unexplained variations. A t-test is a method for evaluating hypotheses that require a population to test an inference.
A t-test examines t statistics, t-distribution values, and the degrees of freedom for statistical meaning to be determined. A variance analysis should be used to carry out a test by three or more methods. The t-test draws a sample from each of the two sets and sets the problem statement by assuming that the two media are identical in zero hypotheses. Based on the relevant formulas, these values are determined and contrasted with the normal values.
The hypothesis considered to be null is either accepted or denied. If the null hypothesis is dismissed, the data readings are high and therefore not due to chance. The t-test is only one of many methods used. To analyze more factors and measures for bigger samples, statistics have to use other tests than the t-test (Standaert, 2018).
The t-test would be used to assess a certain form of data where there are differences between the two media classes. Any of the characteristics vary. Data which is commonly used and which loves to use recorded data, resulting in 100 tossing coins. The t-tests are accompanied by the standard distribution procedure and the unknown variable can be used. Hypothetical evaluation instruments are used to test the theory applicable to a certain part of the population.
| One-Sample Statistics | ||||
| N | Mean | Std. Deviation | Std. Error Mean | |
| Percentage | 10 | 2.9290 | .61374 | .19408 |
| One-Sample Test | ||||||
| Test Value = 0 | ||||||
| t | df | Sig. (2-tailed) | Mean Difference | 95% Confidence Interval of the Difference | ||
| Lower | Upper | |||||
| Percentage | 15.092 | 9 | .000 | 2.92900 | 2.4900 | 3.3680 |
The t-tests use T distribution values. The degree to which the statistical value is determined. To do the test analysis, the variance must be used. T-test aims to provide a measure of the average values of two data sets and to establish the average comparison of values. Null statement of conclusion in t-test where two means are identical. T-tests are commonly used for hypothesis checking in statistics. 3 key data values for the computation of t-test, which comprises the difference between mean values of a data set. The most important dependents of the t-test are the data and form of study needed
Cluster analysis
Cluster analysis or clustering is the process of grouping a series of items so that they are more related (in some sense) to one another than in other groups in the same group (called a cluster) (clusters). It is a major activity of exploratory data mining and a basic statistical data processing technique that is used in many fields, including the identification of patterns, image analysis, the collection of information, bioinformatics, the encoding of data, computer graphics, and computer training.
Different algorithms can be done that vary considerably by learning what forms a cluster and how to locate it effectively. Popular cluster concepts include groups with limited gaps between members of this cluster, dense areas of data space, intervals, or specific statistical distributions. Therefore, clustering can be formulated as an optimization multi-objective problem. Depending on the individual datasets and the desired application of the results, the required clustering algorithm and parameter settings (including parameters like use distance, density, or predicted cluster counts) are determined (Cipresso et al., 2018).
Cluster analysis is not a particular algorithm itself, but the overall task. Cluster analysis is a category of technology that is also known as a cluster to focus cases and to characterize the target. The analysis is another cluster analysis called. This contains a mostly numeric taxonomy. It’s about the cluster category that is referred to as before some single object.
Google employs cluster analysis for various purposes using in-market segments. In this customer satisfaction cluster, the benefits of purchasing the commodity are included. It also contributed to formulating the issue for a certain organization, which selected the selection process and the distance measurement for the different segments by clusters. The study of clusters often uses some types of hierarchical approaches.
Reason for customer participation
Consumers are exogenous for supermarket organizations. In the retail industry, shoppers serve as beneficiaries, and by generating and adding values they are active beneficiaries. Retail associations serve as intermediate individuals, gather manufacturers’ goods, and supply suits. By generating values, buyers have many comparative advantages over the producer. Competitive strategies developed by business segment organizations. Regression is mostly about creating different phrases in different market markets.
The company develops shopping activities for consumers and improves business activities by making different enticing ads. The development of brand values, however, is an important element in improving market activity. The development of brand value has a major effect on the segments which make customers attractive. This method is also called buying mouth or WOM lips or words (Sponder and Khan, 2017).
The creation of market values has higher emissions and the social promotion of products is significantly efficient. Social media have a great deal of promise and deliver low costs and minimum advertising costs. Corporate social media campaigns and advertisements like email marketing were used by various organizations. Digital marketers provide cost-effective advertising to the consumer conveniently with a single click.
Furthermore, social media marketing offers economic returns by making cost-effective advertising activities using a small number of ads. On the other hand, social media gives buyers who publish their offerings in the digital market segments plenty of resources and unlocks new windows. Commercial involvement is linked to consumer reviews directly. For both retailers and consumers, customer input is a key element.
Marketing providers gather data from the consumer reviews which product is customer friendly. Once customer input has been assessed, advertisers can improve customer services. Transliteracy is dependent on consumer input which provides a close connection between consumers and retailers. A company builds a solid client base, providing customer loyalty, to maximize the commitment between consumers and retailers.
Reducing the bounce rate
As an ultimate indicator of a site’s “stickiness” and “appeal,” many site administrators and webmasters pay careful attention to the booning figure and would like to reduce this problem number as soon as possible. Some people also assume that the search rankings will be affected with Google’s recent RankBrain machine learning algorithm. Many advertisers suppose that the problem lies with the quality of a website if their bounce rate is high – whereas real problems can in fact be created before a customer gets a chance to read a page.
Of all the webpage’s challenges, it is perhaps the worst that you still have to launch. After all, how good or poor a user does not interpret (or even see) a site’s content should not matter and 47 percent of consumers want a site to be loaded within two seconds to be loaded, which is important for optimizing the on-page bounce rate to be reduced.
One of the leading factors of e-commerce retailers is the slow-loading of websites. Amazingly, just 2% of the world’s 100 leading ecommerce sites have mobile sites that fully load mobile devices in less than five seconds – and one-fifth takes nearly eight seconds to fully load, almost criminally long for sites which live and die by optimizing the conversion rate.
Google merchandise store analysis using SPSS
The key challenge is to analyze Google Analytics data relating to the Google merchandise storage in a thorough and substantive way and present the findings of our research using SPSS to the fullest use of statistical and data representation capacities. The use of the data in the study is very innovative and accurate with excellent choice of mathematical methods and an excellent and new data analysis. Results are excellent evidence of an excellent knowledge of the use of these methods.
In order to provide straightforward and consistent explanation and proof to link this with the decision-making challenge, the consequences of the data analysis are provided with an outstanding attempt at contextualisation. In the second half of this line, the study definitely addresses a publishable quality. The most busy transaction months are August 2016 to July 2017, October and November 2016. More than every other month, November in particular had a 50 percent increase in transaction amounts.
There may be many explanations for this pattern: A seasonality is an issue or just a random cause. We have no access to past store data to sort that out, unfortunately. But assume the previous years show the same trend. In any case, we might argue that during October and November the Google Merchandise Store is especially busy as Google Merchandise Store offers its items without any advertisements or promotional offers.
Data Findings
Google merchandise brand image through two processes: data sharing and data collection through building user involvement. The most accurate example is consumer reviews in the whole data segments. Any big and medium-sized online store puts pressure on the online market and understands the importance of the online advertisement process and the effectiveness of the consumer. If a client looks for a specific product, the same items from various price points are shown on Google (Chaffey and Smith, 2017).
Meanwhile, Google tracked all consumer behaviors by using the apps that seek those goods. Afterward, consumers will get exclusive items through their emails, SMS, and other social media channels that facilitate the marketing of social media. Big data analysis allows vendors to obtain customer assessment through information on the specific practices of these segments and their customers.
Critical analysis
Google’s overarching market goal is for retail goods from all around the world to be organized and collectively accessible and useful with only one click. Google’s merchandise shop has always set a target of offering products and services to as many people as possible to better their lives. Meg Biron, Media Lab Technology Manager at Google, says that visibility and driving revenue are primary digital marketing priorities.
Biron heads the Google Media Lab, which manages all the media strategies of Google for all the digital promotions of the firm. About every country in the world has access to the Internet with today’s technology development and developments. Of the worldwide 100% of internet requests, 60% were part of Google. The Marketing Officer of Google Spain, when asked about the target demographic, claimed to be their target audience (Google).
This is the same demand for the online goods shop as well. As a result, Google’s digital marketing approach is not exclusive to a specific site or community of people. By taking an approach, big data improve this style of operation. Many companies use Google analysis, which collects real-time data from online segments and produces specific key measures of results. Data can be obtained easily from different online sources, including Twitter, Facebook, and Instagram. These key indicators of success display data from different online platforms which help to define the customary approach by using Big Data Analytics.
Conclusion and recommendation
It can be inferred from these sections that Google analytics uses a standard deviation to calculate corporate principles. The organization’s norm difference is between 50%. Many organizations, according to the group consensus that is obeying big data analytics, have and propose targeted forecasts.
Community views strengthen the market strategy that will eventually provide consumers with goods they would quickly identify products they want to buy. It was noted that organizations with a conventional approach can easily be tackled side by side with digital marketing. Many organizations, who are freely open to the internet consumer segments, can effectively approach the conventional market strategy.
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