Analysis of the performance of my blogs

Data and Digital Marketing Analytics

Student Name: Vardan Arora

Student Number: 10536695

Analysis of the performance of my blogs:

 Home Page Overview

As can be seen, there were 57 sessions out of which 26 were unique visitors. Moreover,  60% of the traffic was from the 'Referral Channel' ie directly from blogger.com. The two countries which contributed to the maximum traffic were Ireland and France as shown in the picture (Fig1). Surprisingly, Monday and Tuesday were the days when the majority of people visited my blog page. 

As shown in fig 1.1, the majority of people accessing my blogs were through a desktop ie. 55%  while 45% of the audience used their mobile phones while reading or accessing my blog page. This shows that mobile visitors are increasing which is a good sign as the website is healthy and can rank in google search.

Fig 1

Fig 1.1

Audience Overview

 In this report, there were 57 sessions out of which 20 were unique visitors who visited my blog. The average session per user is 1:16, which means the user spent a minute to read my blogs. There were 107 page views with a bounce rate of 64.91% (which is quite a lot and can be reduced over time). I am sure with more time and resources all these metrics can be improved.

Acquisition Overview

Acquisition metrics tell us where our visitors came from, such as social media channels, direct channel or referral channels. As we can see, there are Top 3 channels from where the major traffic came. Highest being the Direct Channel with 47% followed by Social Channel with 37.9% and lowest the Referral channel with 15.2% of the overall traffic.

Behaviour Overview

Behaviour overview lets us assess the performance of our content and the actions visitors take on the website. Out of 203 page views, 181 were unique visitors. Average time spent on a page by a visitor is around 2 minutes and 5 seconds. The most frequently viewed blog out my 5 blog was 'The talk of the V's-Three dimensions of Big Data'. 

References:

1. How to Use Google Analytics Behavior Reports to Optimize Your Content

By Kristi Hines Container: Social Media Marketing | Social Media Examiner Year: 2014 URL: https://www.socialmediaexaminer.com/google-analytics-behavior-reports/

2. Top 5 Google Analytics Reports You Should Be Analyzing

By CommonPlaces Interactive Container: Commonplaces.com Year: 2018 URL: https://www.commonplaces.com/blog/top-5-google-analytics-reports-you-should-be-analyzing

Artificial Intelligence in Marketing.

Artificial intelligence and machine learning are now an increasingly integral part of many organizations and industries. However, technology at this moment has become so affordable that smaller companies have started adopting and using AI in every business operation. It has become easier for marketers and companies to get useful insights and anticipate customers' next move to improve customer journeys.

With this in mind, let's discuss and go a bit deeper to know how AI is transforming the marketing industry.

1.    Predictive and Intelligent searches: As technology is becoming smarter it is important to know that the audience is getting smarter too. Thanks to social media and different search engines for simplifying and easing out searches than ever before. With the help of Artificial Intelligence, marketers can analyze these search patterns which will help build a clear picture of their target audience.

2.    Bots: Customer retention and customer engagement is another area where artificial intelligence plays a major role. Chatbots with the help of AI has access to the entire internet’s worth of data, information and search histories making it easier and efficient to build direct-to-consumer relationships.

3.    Campaign Optimization: Machine learning involves the analysis of past consumer data from various business marketing and social channels like social media search, purchase journey, online interaction, etc. The data extracted from all these social channels will allow companies to identify customer behavior and help them optimize future campaigns on the basis of data extracted and in return, it will lead to successful campaign delivery.

4.    Increased ROI: Algorithms for machine learning generate customer insights via predictive analysis, now these insights can be incorporated in the company’s marketing strategy, for example, emails with a personalized message or retargeting the audience on the basis of their demographic or online behavior, etc. This will give a better chance of a higher ROI.

To sum it up, Artificial Intelligence is the Future of Marketing

References

Artificial Intelligence (AI) for marketing | Smart Insights

By  Container: Smart Insights Year: 2020 URL: https://www.smartinsights.com/tag/artificial-intelligence-ai-for-marketing/

What Is Artificial Intelligence Marketing & Why Is It So Powerful? | Emarsys

By  Container: Emarsys Year: 2016 URL: https://emarsys.com/learn/blog/artificial-intelligence-marketing-solutions/

How Artificial Intelligence Is Transforming Digital Marketing

By Jason Hall Container: Forbes Year: 2019 URL: https://www.forbes.com/sites/forbesagencycouncil/2019/08/21/how-artificial-intelligence-is-transforming-digital-marketing/#16a7455421e1

Benefits and Challenges of Customer Data in Marketing

The customers don’t want their data to be collected but at the same time, they respond positively when messaging is highly targeted and personalized. Simply put more data about the customer, the more potential, the more potential is there to create an ideal customer experience, but the more risks are involved from a security perspective. There are several benefits and challenges using customer data in marketing from catering to customer preferences, ensuring relevant communications to privacy concerns, data usage restrictions, etc. 

Img Src: https://risnews.com/careful-customer-king

Here are a few benefits of customer data in improving 360-degree customer experience.

1.     Customer Sectionalization: Collecting buyer data allows organizations to not only engage existing customers with relevant information but also creates a buyer journey for a more personalized user experience.

2.     Customer interests:  Collecting customer data can be an effective way for an organization to show that they care about you. Moreover, this allows the organizations to align their communication keeping in mind the interests of the customers. 

3.     Maximizing ROI: With keeping in mind about customers interests, customers taste and preferences and buyers’ journey this will not only help organizations to gain valuable insights, but it will also help organizations to maximize their ROI

Here are some challenges of using customer data in marketing:

1.     Commitment: To gain all the benefits of consumers' data, organizations must be committed to delivering the best of their results. If they fail to do so, then it doesn’t make any sense for the companies to even formulate their marketing strategies.

2.     Finding the right team: Due to the complexity of jobs and skills required, it is quite challenging for employers to attract the right employees that specialize in audience engagement or predictive analysis. 

3.     Integration: When organizations fail to the integration process, becomes difficult for marketers to collect the correct data to formulate their marketing strategies. For instance, eCommerce businesses and retail businesses usually gather customer data from social media and other mobile marketing campaigns.

 References:

1. Using Customer Data for Marketing: The Good, Bad & Ugly

By Omer Minkara Container: Aberdeen Year: 2014 URL: https://www.aberdeen.com/cmo-essentials/good-bad-ugly-using-customer-data-for-marketing/

2. The Benefits and Challenges of 360 Customer Data - Primacy | Blog Primacy | Blog

By  Container: Theprimacy.com Year: 2019 URL: https://www.theprimacy.com/blog/the-benefits-and-challenges-of-360-customer-data/

3.Data-Driven Marketing: Benefits, Challenges, And Examples | Infotanks Media

By  Container: Infotanks Media Year: 2019 URL: https://www.infotanksmedia.com/blog/data-driven-marketing-benefits-challenges-and-examples/

Big Data for Marketing

Big data refers to the increasing volume, velocity, veracity, variety, variability, of information. With the advancement of technology, big data has become a powerful tool for all the marketing companies working and operating in this digital era. It has helped the marketing companies to refine their strategies, improvise decision making and helped them understand the customer needs in a more refined and in an organized way. 

Firstly, let us take a moment to think about how customer data was collected 15-20 years ago- POS transactions, coupon redemption, mass email campaigns etc. Then think about how customer data is collected today- online purchase data, click through rates, social media behavior, browsing patterns, geolocation etc. In my opinion, there’s no comparison. 

Why Big Data matters in Marketing?

In marketing, it’s the insights extracted from big data, the decisions you make the actions you take, makes all the difference. When it comes to CRM (Customer Relationship Management), it depends on how investments made in the systems can be enhanced, in addition to strategies for increasing customer retention, conversion rates, customer engagement etc. By combining big data strategies, marketing companies can make a substantial impact in the following areas.

1.    Customer Engagement: By analyzing and extracting big data information, it will not only give an insight about who your customers are, but where they are, what are they up to and how do they want and when do they want to be contacted.

2.    Customer retention and loyalty: Big data will help the organizations to discover what influences customer loyalty, what keeps them engaged and what keeps them coming back to the website again and again.

3.    Marketing Optimization: With the help of big data we can determine optimal marketing spend across all marketing channels, as well as continuously optimize different marketing programs through testing, measurement and analysis.

Three types of Big Data that are ideal of marketing perspectives.

1.    Customer:  With the help of Big Data, behavioral, attitudinal and transactional metrics of the customers are collected from sources such as marketing campaigns, point of sale, website, customer surveys etc. 

2.    Operational: Big data here can help to measure the quality of marketing processes which include marketing operations, resource allocation, budgetary controls etc. 

3.    Financial: Big data can help to measure the financial health of the organization such as sales, revenue, profits and other financial objectives. 

One real Life example of Big Data in Marketing

1.    Elsevier- is the world’s largest provider of scientific, technical, and mechanical information publishing 43,0000 peer reviewed research articles annually uses big data to closely track journals, books throughout their life cycle in an efficient way as these articles come from wide variety of resources present across global organizations.

Resources: 

Big Data, Bigger Marketing

By  Container: Sas.com Year: 2020 URL: https://www.sas.com/en_ie/insights/big-data/big-data-marketing.html

Big Data in Marketing 101 & Why it's Important

By Shana Pearlman Container: Talend Real-Time Open Source Data Integration Software Year: 2019 URL: https://www.talend.com/resources/big-data-marketing/

Ten Ways Big Data Is Revolutionizing Marketing And Sales

By Louis Columbus Container: Forbes Year: 2016 URL: https://www.forbes.com/sites/louiscolumbus/2016/05/09/ten-ways-big-data-is-revolutionizing-marketing-and-sales/#35f606a721cf

The talk of the V's: Three Dimensions of Big Data explained.

What is Big Data?

A large and complex amount of data is collected by businesses these days. The data collected is so expansive that traditional data processing software cannot manage them. However, these enormous volumes of data can be utilized to address business problems or issues that businesses couldn’t even tackle before. A large part of values that companies offers, comes for the data they collect which constantly helps them to analyse and produce and develop new products

The Three dimensions of Big Data:

1.     Volume: It refers to the large amount of data that is processed every second from different sources such social media, websites, credit cards etc. The benefit gained from processing such substantial amount of data is the main attraction of big data analytics. The vast amounts of data have become so huge that it is nearly impossible to store or to analyze them using traditional data collecting techniques. Collecting such huge amount of data has become a challenge for companies, as modern data collecting techniques and software’s are required to analyze and process such data.

2.     Velocity:  The importance of data velocity is the rate at which the data is flowing in an organization. Every day the number of clicks, number of emails, messages, pictures etc that are sent through websites or mobile applications should be instantaneously processed and analyzed so as to allow the organization to make quick decisions as well as to think about how this data can be implemented to give rise to futuristic discoveries. It’s not just about input data that matters, it is also about the velocity at which systems generate outputs too.

3.     Variety: It’s not just about contact information or addresses it is much more than that. The variety of information that is collected from the user these days has totally changed as it was being collected in the past. More than 80% data that is collected is unstructured. New and innovative technology is being implemented to analyze such structured and unstructured data. 

References:
1. Volume, Velocity, Variety: What You Need to Know About Big Data

By O'Reilly Media Container: Forbes Year: 2012 URL: https://www.forbes.com/sites/oreillymedia/2012/01/19/volume-velocity-variety-what-you-need-to-know-about-big-data/#2f11e2ff1b6d

What Is Big Data? | Oracle Ireland

By  Container: Oracle.com Year: 2014 URL: https://www.oracle.com/ie/big-data/guide/what-is-big-data.html