I REPORT Student Name/Number: Elina Kochenko / 10532850, Marilia Martins / 10532756, Sedca n Altundal / 10533549 Course Title: MSc in Digital Marketing Lecturer Name: Naomi Kendal Module Title: Data & Digital Marketing Analytics Assignment Title: Digi tal Audit an Analysis of T he O nline Performance of Website and S ocial M edia P latform Word Count: 3292 II TABLE OF CONTENTS 1. EXECUTIVE SUMMARY ................................ ................................ ................................ .......................... 1 2. BUSINESS OVERVIEW ................................ ................................ ................................ ............................ 1 3. TARGET AUDIENCE’S OUTILINE ................................ ................................ ................................ ............. 1 3.1 Persona Identification ................................ ................................ ................................ ......................... 2 4. AUDIENCE ANALYSIS & INSIGHTS & RECOMMENDATIONS ................................ ................................ .. 5 5. ACQUISITION ANALYSIS & INSIGHTS & RECOMMENDATIONS ................................ ........................... 12 5 .1 Channels ................................ ................................ ................................ ................................ ............ 13 6. BEHAVIORAL ANALYSIS & INSIGHTS & RECOMMEND ATIONS ................................ ............................ 17 6.1. Content Analysis ................................ ................................ ................................ .............................. 17 6.2. Landing Pages & Exit P ag es Analysis ................................ ................................ ................................ 21 6.3. Event Analysis ................................ ................................ ................................ ................................ .. 24 7. CONVERSION ANALYSIS & INSIGHTS & RECO MME NDADIONS ................................ ........................... 25 8. GOOGLE ADS ANALYSIS & INSIGHTS & RECOMMENDATIONS ................................ ............................ 27 9. SOCIAL MEDIA ANALYTICS & RECOMMENDATIONS ................................ ................................ ........... 35 9.1. Twitter Analysis of the Landscape and 4Securitas ................................ ................................ ........... 36 9.2. LinkedIn Analysis of the Landscape and 4Securitas ................................ ................................ ......... 41 10 SEO AUDITS & ADDITIONAL RECOMMENDATIONS ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... 45 1 1 BIBLIOGRAPHY ................................ ................................ ................................ ................................ 50 1 2 APPENDIX ................................ ................................ ................................ ................................ ........ 52 1 1. E XECUTIVE SUM MARY This paper analyze s and present s 4Securitas ’ website ’s performance using Google Analytics metrics It includes an overview of 4Securitas , target personas, and analyses from 1 /09/ 2019 – 1 /03/ 2020 . It examines , including insights and recommendations for each section , for the following Google Analytics dimensions : Audience, Acquisition, Behavioral and Conversion Report Analysis ; in addition to Google Ads, social media analysis and SEO audit R eferences and appendix conclude 2. BUSINESS OVERVIEW 4Securitas is an Irish start - up , on the market since March 2017, specializing in cybersecurity automation and AI. 4Securitas create d Automated Cybersecurity Interactive Application (ACSIA ) system , which affordably si mplifies cybersecurity. ACSIA is an automated inte l ligen ce defence system which monitors and captures intrusion endeavours from automated hacking devices and manual techniques. When an intrusion is identified, the system alert s and produces a real - time inc ident report. 3. TARGET AUDIENCE ’ S OUTILINE The targ e t audience are decision - makers in cyber or IT security departments , within the IT, energy, and governmental sectors. The y are usually a Chief Technology Officer, head of IT and/or cyber security, C hief I nfo rmation S ecurity O fficer (CISO ), etc . T he t a rget a udience is aware of the need to monitor and protect servers . T hey constantly analyze and evaluate risk s t o assets They may have difficulty storing data reliably and finding software. They desire a trusted expert partner with strong technical experience, 2 w ho guarantees operations ’ security and simplifi es reports and storage with a portfolio of services. 3.1 Persona Identification Persona 1 A potential customer i s Alstom Ireland and the UK company. T he Sec urity Operations Manager handles cybersecurity iss ues His insights are displayed i n Figure_ 3.1. Figure_ 3.1 – James Wood persona 3 Persona 2 Benjamin Kats is CISO of a medium business , manag ing IT department and cyber risks. He communicates information ab out data security to nontechnical collaborator s Figure_ 3.2 – Benjamin Katz persona 4 P ersona 3 Curve App is a F intech start - up offer ing all bank cards in one card and app product. It is a highly regulated sector, and Curve App holds sensitive user i nformation , making it a potential customer. Fig ure_ 3.3 – Laura Donovan persona 5 4. AUDIENCE ANALYSIS & INSIGHTS Figure_ 4.1 — Audience Overview As a B2B company, the 6 - month Audience Overview (1/09/2019 – 1/03/2020) reveals visitor number s drop dram atically at weekends ( See Figure_ 4. 1; 4. 2 ) Fig ure_ 4.2 — Active Users , 15 /02/2020 - 17 /03/2020 6 Recommendations: i. As people tend to spend more time o n social media (SM) during weekend s , consider using SM channels more actively during weekends to increa se traffic. 4securitas webpage receives 300 visito rs monthly (S ee Figure_ 4.3) Figure_ 4.3 — Monthly visitors, 1 /11/ 2019 – 1 /02/ 2020 Figure_ 4.5 — Audience Overview S ix months’ bounce - rate (1 /09/ 2019 – 1 /03/ 2020) is 63.3% ( See Figure_ 4.5 ) . Due to our ni che sector and low visitor number s , Analytics Benc hmarks was not available to assess performance. However, t he average bounce - rate for ‘ Business & Industrials ’ category websites is 50.5% (Costumedialab , 2020; CXL , 2020) B enchmark data indicates a need to reduce our bounce - rate 7 Recommendations: i. Do keyw ord research and optimize the landing pages with high bounce - rate to increase quality traffic and keep users on the website ii. Critically assess website ’s design , placement of CTAs and navigations to increas e user - friendliness and persuasiveness Use testim onials R eturning visitors are 14.8% Average 1.8 pages are viewed each sess ion. As B2B websites ’ average rate is 2 pages (Hinge, 2020) , this metric does not show urgent action is necessary ( See. Figure_ 4 6 ) Most visitors are from (in order) Ireland (18% ) , USA (14%), Italy (10%), France (6.6%), India (6.4%) and U K (5.4%). Average bounce - rate for USA visitors is 83%, for overall visitors it was 63%. Other s with ha ve higher than average (63%) bounce - rate s are Germany (75.8%) and Netherlands (71.3%). Fig ure_ 4.6 — Visitors by Countries , 1 /09/ 2019 – 1 /03/ 2020 8 Recommendat ions: i. Bu il d landing pages to specifically target countries with high er bounce rate and run search ads. ii. Do keyword research for these co untries , optimize and localize the co ntent of the landi ng page s for search engines. For instance , for USA visitor s , when bounce - r ate s are filtered by “exit pages”, the Home page an d ‘Indicators of Compromise (IoCs)’ product page have significantly higher bounce - rate s (despite high visit or number s ) See Figure_ 4.7. Figure_ 4.7 — Top Pages Causing High Bounce - rate for USA 9 Re commendations: i. O ptimiz ed pages with higher than average bounce - rate s ( Home page and IoCs product page ) N o conversion action s or value s w ere defined or measu red , during the period we had website access Therefore, we are not able to see the va lue s for visitors by locations, age , etc. Actions: i. After analyzing the busi ness and website, we set up conversions (goals & events) for key action (e.g. video plays, cli cks for free trial / buy now / contact us / LinkedIn icon ). Most visitors are 25 - 34 - years , followed by 35 - 44 - years ; no significant difference between male / female users was found ( See Figure_ 4.8 ). Figure_ 4.8 — Age and Gender Visitor Distribution 10 Segments wit h higher interest in our business / offers are Employment (18.4%), Business Services (1 5.9%), Software/Business & Productivity Software (10.7%), Financial/Investme nt Services (7.6%), Business Services/Advertising & Marketing Services (7.1%), Enterprise Softwar e(6.6%). See Figure_ 4.9. Figure_ 4.9 — Audience Interest Overview, 1 /01/2020 - 17 /03/ 2020 Recommendations: i. Target in - market segment s through ad tactics (e.g. S EM) and optimize creative s and messages accordingly. Since in - market segments are lower in the purchase funnel, and have greater interest in our products, communicate special offers and use call to actions (CTAs) 11 ii. Target ‘ Affinity Category S egments ’ and r efine content when targeting (e.g. m ore branding , display ads , educating content etc. ) to incre ase awareness about 4 S ecuritas. The overwhelming majority of visitors use desktops (83.7%). Our B2B sector dynamics (e.g. people engage with us when in their offices) may help explain this rate . However, page/session average is also lower for mobile (1. 78) than desktop (2.11), indicat ing low mobile traffic is also about the mobile experi ence provide d Figure_ 4.10 — Device Distribution Recommendations: i. Test the website’s mobile - friendliness score , o ptimize for mobile (Spee d, e.g. images , design ) ii. Run Google Display Ads and target mo bile ap p s whi c h Affinity and I n - market seg ments ar e lik e ly to use. (e.g. Financ ial Ser vice Ap p s ) 12 5. ACQUISITION ANALYSIS & I NSIGHTS The a cquisition section provide s an ov e rview of the website ’s traffic , enabling analy sis of where the traffic is coming from The data show s visitors who reached the website throu gh Organic Searches, Direct, Referral, Social and other cases. B elo w are the acquisition s during 1 /09/ 2019 – 1 /03/ 2 0 20 Figure_ 5.1 — Acquisitio n Overview 13 5. 1 Channels Figure_ 5.2 — Channels Overview 1) Direct: M ajority of users [ 844 users (48.6%) ; 8 41 were new users ] , came from direct acquisition D irect acquisitio n , follow ed by organic channel, had the highest b ounce - rate (70 83%) and longest average session duration See Figure_5.2. It should be noted that Google Analytics may misinterpret some ses sions as ‘ Direct Traffic ’ Insights: In direct traffic cases , we l ack information / parameter s on what caused the us e r to visit the website Nevertheless , k nowing which pages visitors go directly to , allows 4Securitas to design those pages strategically A s the goals w as created on 09/03/2020 , it was not possible to trac k goals and conversions 2) O rganic Search r epres e nt s a significant traffic volume ( 38 1% ) , reaching 709 users and yielded a significant bounce - rate ( 58 81% ) According to search analys is on Console 2020 , the k eyword s ‘ 4Securitas ’ had 173 click s with 262 im pression s and ‘ acsia ’ had 1.033 impressions T he performance k eywords showed room for 14 improvement and should be more service specific and target specific , as those keywords generate the mos t revenue ( S ee Figure_ 5.3) Figure_ 5.3 — Search Console 3) Refe rral: 4Securitas ’ referral traffic comes mainly f rom linked I n.com ( 49 users ) , followed by blog.acsia.io ( 42 users ) and media.acsia.io ( 38 users ) italy.cybertechconference.com have highest average page views (3.16) , a n excellent engagement (See Figure_5.4 ) The content/sites hosting these backlinks are r elated to relevant topics for 4Securitas (e.g. cybersecurity) Facebook and intranet are the last acquisition (sending only 10 15 users each) Facebook and baidu.com both have 100% bounce - rate L ongest time spe nd was 3 07 on italy.cybertechconference.com Figure_ 5.4 — Referral Traffic 4) Social Media : Compared to other channels, SM channels require improvement to increase engagement SM ha s 67 users' acquisition and a 58% bounce - rat e; shared 16 among LinkedIn (50 users ) , Facebook (11) and Twitter (6). Linke d In brings 58% of new users from SM and 40% of new users from SM referral See Figure 5.5. Figure_ 5.5 — Social Media Overview According t o the below Users Flow , c hannel s with greatest interacti ons are Lin kedIn , then Facebook and T witter Figure_ 5. 6 — Social Network in Journey Path 17 5) Other h as the least acquisition users (0.38%) , and lowest bounce - rate ( 28 57% ) Recommendations: i. I mplem enting M eta R eferrer T ag and building custom segments could improve referral traffic. ii. T o improve the acquisition r e port ’s precision , improve SEO strategy , using TAG Manage r , as it is the recommended way to implement advanced e - commerce (given the site ’s e xcellent organic performance ) iii. P ersonali s e website experience usin g smart content Utilizing specific keywords cou l d improve performance and increase traffic iv. O nce the Goals ’ ( set up using CTA ) results are produced , 4Securitas will be able to analyse conv ersion results to establish which channels need more investment 6. B EHAVIORAL ANALYSIS & I NSIGHTS 6.1. Content Ana l ysis To perform content analysis a dashboard with metrics was created. The data is grouped into 3 main sections: Acquisition / Engagement an d SM Impact. 1) Acquisition was analyzed through Google Search Tr affic, SM Traffic, Web Referral Traffic, and New Users by Landing Page metrics. Figure_ 6.1 shows data for 1 /09/ 2019 – 1 /03/ 2020. 18 Figure_ 6.1 — Dashboard Acquisition According to Google Se arch ’s Traffic R eport , the landing page receiv ed the highest user n umbers from Google Search clicks (593), and SM l i nks (57). 2) Engagement was analyzed by understanding how satisfied users are with the content’s quality via the most viewed pages, time o n page and exit pages metric s