Google Merchandise Store Analysis

This report analyzes various custom reports for Google Merchandise Store Demo Analytics account for paid search analysis and offers recommendations to improve the Merchandise Store.

Running head: GOOGLE ANALYTICS REPORT 1
Google Merchandise Store Analysis
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Section 2
Introduction
Google Analytics is an important tool for running AdWords campaign. It does not only
measure how much traffic a website is getting, the site’s top pages, traffic sources and marketing
efforts, there is even a much better use of Google Analytics. It is equally essential in improving
websites to convert more visitors into leads, sales and even subscribers. Despite its overreaching
significance, Google Analytics can be discouraging sometimes. This is due to the fact that they
are created for everyone and are seemingly stuffed with endless reports as anyone may need but
they gratify no one in the end unlike custom reports which are tailored for specific functions with
sets of controls to ensure that they do not deliver data but instead convey insights. This document
seeks to analyze various custom reports for Google Merchandise Store Demo Analytics account
for paid search analysis and offer recommendations to improve the Merchandise Store.
Organic search and paid search
Organic search is a search which is primarily based on natural rankings which are not
paid for, the rankings are determined by search engine optimized by various Search Engine
Optimizer SEO practices. Paid search, however, allows individuals to pay for their websites to be
displayed in the search engine when a specific phrases or keywords is typed on basis of either
clicks or views of the ads. Strong marketing strategies, however, utilizes both paid and organic
searches in order to be available online.
The Search Engine Optimization SEO have a better part of the source of traffic for
Google Merchandise Store most of which come from Google and Bing. Such a great amount can
be gained from the bounce rates on SEO points of arrival, the Per Visit Goal Value conveyed, the

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content's format, viable suggestions to take action thus substantially more from the search engine
optimization SEO dataset.
In like manner, the mystery endowment of Paid Search is that it gives the opportunity to
control the client's experience, as opposed to the SEO. Additionally, it offer an opportunity to
choose what the word phrase is. What the ad copy is can also be chosen as well as the landing
page experience. There are significant amount of outcomes that can be gained from this
controlled procedure that would then be pivoted and actualized on whatever is left of the web
experience.
It can be seen how the two reports can lead to issues and opportunities as well. It is
however advisable that when pay per click PPC bounce rate is higher compared to the organic
visits, it would be good to check the system and find out any problem which might be the course
of the bounce rate. This is due to the fact that the traffic is paid for and should therefore generate
more leads than the organic search, thus it should not leave the site at a higher rate.
Paid search campaign
Normally, when logging into AdWords, add keywords and key elements, matches are also
selected. The bids are then matched to relevant queries depending on the choice of phrases. Ads
do not always show up for keywords but show up for the matched search queries. As a result, the
real optimization cannot just get achieved by doing the key word analysis of the AdWords
campaign but it comes from the understanding of the matches of the user queries and the words.
 Checkout Abandonment Rate: is known as the percentage of the visitors who have
experienced the checkout procedure however did not proceed with the buy.

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 Truck Abandonment Rate: is the percentage of guests who added things to their trucks
yet left the site without continuing to checkout.
 No Cart Addition Rate: this refer to the percentage of guests who had item see sessions
yet did not add anything to their truck.
Figure 6: paid search traffic with match key words
A good example is shown in the screenshot from the analytics. In the figure 6, we would bid on
the key word “Google Merchandise store” and it can be seen that the actual user queries that the
words were matched with got somehow verified because of the words which structured the
campaign for example “Google Merchandise” and “Google Hats” shown in the figure above as
shown in the “Google Ads keywords” report. The view presented in the figure is just but a broad
match. One good thing about the report is that it helps in showing the exact match users queries
at a zero percent conversion rate which is surprisingly rare for exact match. Afterwards, we can
get to the phrase match.

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Section 3
For the purpose of this analysis, a Google account was created which further helped in
creating a Google Analytics account. Using Google Analytics account, reports for Google
Merchandise Store were downloaded for use in documenting this report.
E-commerce overview report
As at 13th October 2018, the top performing product at the Google Merchandise Store
was Google flat front bag grey shown in figure 6 in appendix section. The Google flat front bag
grey is also the top performing product category leading with 7.94% according to the “E-
commerce overview” report. Its presence in the homepage is probably the reason for its
performance among other merchandise. According to the Google Analytics, 1.17% of all users’
sessions resulted in an e-commerce transaction leading to 230 total number of transaction as
shown in figure 1.
Figure 1: E-commerce report screenshot

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If the Google flat front bag grey emerges the best among the sales of the day at the
homepage of the website, how much more sales can the product generate when optimized with
on-site search? It is important to optimize the top landing pages due to the fact that they always
get much more traffic and are the first pages which visitors arrive at on a website. The chances
are that the visitors will leave the site if they fail to find what they are looking for within five
seconds.
The site can be improved for more sales by analyzing landing pages reports for the last
thirty days and then see which pages with the highest bounce rate out of the top ten pages and the
pages which have the conversion rates lower than the average goal of the website which are the
indicators of poorly performing pages on a website. The poorly performing pages will then be
optimized first by improving their headlines, call-to-action, imagery and benefits. When these
pages are optimized, the visitors’ engagements and the chances of the visitors for the key goals
of the website will be increased.
Shopper journey by goal flow report
The report shows lost opportunity. Out of the 2.3 K who managed to reach at the cart
page, only 699 users managed to exit the funnel of which 477 users exited from the basket page
as shown in the “Goal Flow” report. This must be due to the users who does not have their
google account and are not willing to create the account. The first time an estimated shipping
cost up is the basket page, it can therefore lead to potential buyers to drop off. Of the population
which reached billing and shipping stage, only 20.9% moved to payments (see figure 2).

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Figure 2: shopper journey by goal flow report
Channels that leads to conversions report
Upon analysis, it was found that the paid search and social network were almost
becoming the final interaction channels meaning that they closed more sales compared to the
assisted sales as in the “Channel” report. Organic, direct and referral on the other hand have
equally contributed to the assisted and final conversions. The display is essential in assisting
instead of closing conversions as shown in figure 3.

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Figure 3: Channels leading to conversions a little better
In order to fully understand this data it is important to juxtapose it against the conversion
path data as in “Top conversion paths” report (see figure 4).
Top conversion paths
Figure 4: The top conversion paths

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It can be deduced from the top conversion paths that the referrals and organic searches
are the predominant first interaction channels for conversions while other advertising is the last
interaction channel. Due to the percentage conversions, optimizing as well as channelizing spent
on the channels could lead to a higher ROIs.
Analysis of shopping behavior report
Shopping behavior report refer to the manner in which customer’s progress through each
step into purchasing merchandise. It is essential in the sense that it aids in identifying the pages
with high abandonment rates that needs improvements. According to the “Shopping behavior
analysis” report, it is more likely that the returning visitors reach checkout sessions and make
transactions. The highest number of transactions and the highest number of product views
completed by users that come through googleplex referral sources are as a result of the organic
sources (Google analytics, 2018). Additionally, the checkout abandonment is low through the
googleplex referrals. The source google analytics percentage shows that abandonment is high as
shown in the following figure.
Figure 5: shopping behavior report

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Recommendations
Various recommendations can be derived from this analysis. The recommendations are
categorized into two including the recommendations regarding improvement of shopper
experience and the recommendations to close more transactions.
Improvement of shopper experience
 The organization should make login easy or remove it due to the reason that more buyers
are get lost with high intent on the login step.
 For the Google Merchandise Store to be successful, the organization’s system must push
only relevant users through the funnel, with the billing and shipping at the top of the
funnel.
Closing more transactions
 It is recommended that the organization develop micro-segments of users that were left
out at some points of the funnel and provide them with customized campaigns in order to
achieve its business goals.
 It is imperative for the enterprise to optimize the channels and two leg path that offers
maximum conversion.

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References
Google, (2018). Google Merchandise Store. Retrieved on 13th October 2018 from: <
https://your.googlemerchandisestore.com/index>
Google analytics, (2018). Shopping behavior analysis. Retrieved on 13th October 2018 from: <
https://analytics.google.com/analytics/web/?
utm_source=demoaccount&utm_medium=demoaccount&utm_campaign=demoaccount#/
report/conversions-ecommerce-shopping-behavior/a54516992w87479473p90822334/>
Google Analytics, (2018). Google Ads keywords. Retrieved on 14th October 2018 from: <
https://analytics.google.com/analytics/web/?
utm_source=demoaccount&utm_medium=demoaccount&utm_campaign=demoaccount#/
report/advertising-adwords-keywords/a54516992w87479473p90822334/>
Google Analytics, (2018). Top conversion paths. Retrieved on 13th October 2018 from: <
https://analytics.google.com/analytics/web/?
utm_source=demoaccount&utm_medium=demoaccount&utm_campaign=demoaccount#/
report/bf-top-conversion-paths/a54516992w87479473p90822334/>
Google Analytics, (2018). Goal Flow. Retrieved on 13th October 2018 from: <
https://analytics.google.com/analytics/web/?
utm_source=demoaccount&utm_medium=demoaccount&utm_campaign=demoaccount#/
report/goal-flow/a54516992w87479473p90822334/>

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Google Analytics, (2018). Channel. Retrieved on 13th October 2018 from: <
https://analytics.google.com/analytics/web/?
utm_source=demoaccount&utm_medium=demoaccount&utm_campaign=demoaccount#/
report/acquisition-channels/a54516992w87479473p90822334/>
Google Analytics, (2018). Channel. Retrieved on 13th October 2018 from: <
https://analytics.google.com/analytics/web/?
utm_source=demoaccount&utm_medium=demoaccount&utm_campaign=demoaccount#/
report/conversions-ecommerce-overview-beta/a54516992w87479473p90822334/>

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Appendix
Figure 6: the google flat front bag grey