Capturing Your Audience Early, With Video

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Capturing Your Audience Early, With Video

By: Bill Gaulke

Need to grab your audience’s attention right away? The solution is simple and is becoming a bigger and bigger trend. That trend is, video content. In a Forbes article titled ‘Four Emerging Digital Marketing Trends To Keep On Your Radar’, by Nick Brukner, Brukner states “social media platforms have altered their algorithms to favor video content. Now, social users are seeing fewer photos first and immersing themselves in the black hole that is the endless scroll of a video playlist. With the uprise of video impressions and shares, some pages create video slideshows out of still images in hopes of beating the news feed algorithm.” So, what does this all mean. Less photos, more video. Video allows for your message to be portrayed faster, by providing more insight to your product or business. It should also be noted that statistically speaking, videos are being watched at a rapid pace. As a matter of fact, 100 million hours of video are being watched on Facebook every day, and Instagram, Twitter and Snapchat generate billions of video views every day, as per Brukner’s report.

Now, with an understanding that video is becoming an increasingly bigger trend. Why such a demand, for video? 52% of marketing professionals across the globe feel that video is the type of content with the best ROI. With the younger demographic viewing video on a wider range of devices than ever before, 2018 will be an important year for brands to capitalize on video advertising to market their products and services, this according to Sara Dyer’s article, ‘2018 Digital Marketing Trends: What’s Next for Video Marketing’. For my own personal perspective, while on social media, my preference is to view videos over photos. This is because videos peak your interest, they show demonstrations that a still photo can only insinuate. Dyer’s article also touches on the use of Live-Streaming. Having seen many companies live-stream their product(s), it never dawned on me that this could very well be, the future of commercials, and it happens LIVE! Think about it… Immediate customer interaction, through chat. Immediate sales, based off seeing live usage of a product. AMAZING!

Customer interaction, sales and product demos. These are just a few benefits, that can arise from the demand of a trend. But let’s take a look at some more benefits, of incorporating video content. From a marketing strategy standpoint, adding video can be beneficial in a number of ways. Kirk Donovan outlines six benefits of using video marketing, to promote your business. Those six benefits, include:

  1. Increase Conversions on your Website.
  2. Increase Click-Through Rates.
  3. Improve Brand Recognition and Awareness.
  4. Videos easily adapt to Multiple Device types and Platforms.
  5. Improve your Websites SEO.
  6. Videos Have the Potential to go Viral.

When you look at these six benefits, what do you think? To me, I immediately think, “these six benefits could very easily be the same benefit or goals, at any given time”. Meaning, your goal is to always increase conversions; click-through rates; broadcast your brand. But with the use of video content, and the understanding that how many videos are viewed daily, through social media, you can set out to accomplish all six benefits and then some.

One must keep up with digital marketing trends, in order to be able to be a trend of their own.


Brucker, N. (2018, March 06). Four Emerging Digital Marketing Trends To Keep On Your Radar. Retrieved April 25, 2018, from

Enterprises, K. D. (2017, December 6). Top 6 Benefits of Using Video Marketing to Promote Your Business. Retrieved May 1, 2018, from

Dyer, S. (2018, February 01). 2018 Digital Marketing Trends: What’s Next for Video Marketing. Retrieved April 26, 2018, from

Using Data Analytics to Improve the Customer Experience

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Using Data Analytics to Improve the Customer Experience

By: Robert Morris

The customer experience (or CX for short) is a hot topic these days and companies are spending a lot of time studying and mapping their customer journey using data analytics.  To step back, there are many definitions of what defines the customer experience.  One definition that I particularly like is Forrester Research’s – “How customers perceive their interactions with your company.” Companies are always looking at ways to improve their customer’s perception of themselves as this allows them to attract and retain customers.  If that doesn’t help to explain what makes the customer experience important, research performed by Forbes indicates that more than half of customers today indicate that they have switched companies or service providers due to a bad user experience.  Companies need to find ways to limit these bad experiences; CX analytics tools are one way that they can do this.   

According to an IBM whitepaper, Five Best Practices for Understanding Customer Journeys, 81% of consumer brands say they have holistic views of their customers but only 37% of customers believe that their favorite retailer understands them.  This is a big difference.  Companies need to take the time to better understand their customers and analytics tools allow them to do this.  With CX analytics tools, companies are able to collect and analyze data that helps them to understand their customers better.  They are able to gain knowledge and form insights about what their customers are looking for.  One way that they are able to do this is by looking at and analyzing data that has previously been left untouched. 

Many sources, including IBM, estimate that approximately 80% of data can be classified as Dark Data, which refers to data that is not being used.  Companies are beginning to take a look at this Dark Data to determine how it might be able to help them improve their customer experience.  Some examples of Dark Data that companies are now beginning to look at include data from social media network, web analytics, email messages, etc.  Companies are beginning to leverage CRMs and other applications that can pull data from all of these sources together and help them to form insights on how to attract new customers and retain the ones that they currently have.  Companies are beginning to realize the value of this data that is sitting unused in various applications and they are starting to take a look at what they can do with this data. 

In a Garner Study, it is indicated that by the year 2020, customer experience projects will make up at least 40% of all data analytics projects.  Because of this, many software companies are racing to refine and develop new applications that companies can use as a tool for these projects.  The field is becoming very crowded with different types of software that can help companies to collect and use their data in ways that will help them to attract and retain customers.   The types of solutions that help businesses to achieve these results include CRMs such as Oracle and Salesforce, web analytics tools such as Google Analytics and IBM Tealeaf, and ticketing systems such as Zendesk and FreshDesk.  Companies that have discovered the benefits of CX analytics are finding ways to combine data from multiple applications and sources and using this information to create a holistic view of their entire customer journey. 

Personalization is also a large piece of the customer experience and customers are beginning to expect a personalized experienced from companies that they are working with.  Creating portals, dashboards, email marketing strategies, etc. that are personalized to each customer help companies to retain their customers and gain more revenue from their current customers.  According to a study by Marketing Land, personalized emails to customers deliver six times higher transaction rates!  Companies need to take advantage of the data that they have and tools that are available to them to create a personalized marketing plan for each of their customers.   In the past, it may have been difficult and time-consuming to do this, but with the powerful tools available today, there is no reason not to. 

Sources Cited

Forsyth, A. (2017, June 14). Data is everywhere and that’s a good thing. Retrieved December 10, 2017, from

Gesenhues, A. (2014, July 22). Study: Personalized Emails Deliver 6X Higher Transaction Rates, But 70% Of Brands Fail To Use Them. Retrieved December 10, 2017, from

IBM. (2017, June 19). Five Best Practices for Understanding Customer Journeys. Retrieved December 10, 2017, from

Ingelbrecht, N., & Huang, O. (2017, March 30). Survey Analysis: Customer Experience Innovation 2017 — AI Now on the CX Map [White paper]. Retrieved December 10, 2017,

Manning, H. (2017, July 12). Customer Experience Defined. Retrieved December 12, 2017, from

Newman, D. (2017, April 04). Improving Customer Experience Through Customer Data. Retrieved December 10, 2017, from

Data Socialization

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Data Socialization

By: Samantha Diersen

A current and emerging trend in analytics is Data Socialization. Data socialization is the process of making data easily accessible to and understandable by regular people in an organization (Joshi, 2017). This is a shift from previous practices in analytics, and streamlines the process.

Previously, specific departments or people within an organization handled the collection and analysis of data to glean insights. Employees in these departments would have field specific education and language, as well as a strong understanding of statistics. The general insulation of the departments encouraged the use of these terms, but created a ‘language barrier’ when it came to dealing with outside departments or supervisors. When statistics are not properly explained in terms that all parties understand, it inhibits mutual understanding. Consequently, confusion results when employees specializing in the collection and analysis of data attempt to present new or updated findings to supervisors or outside departments (Sharma, 2017).

The process of shifting to data socialization and removing the barrier in organizations started with the idea of data democratization. Data democratization is ability of data to be available and “accessible to the average end user” (Rouse, 2017, para. 1). This distributes data throughout the business for individuals to manipulate and gain insights from it. Advancements in virtualization and cloud storage made data democratization possible. This allows applications to store and manipulate data without the technical details like formatting, and to share it in real time (Rouse, 2017).

Data socialization takes user demand and advancements, and expands on the concept of data democratization. The sharing culture of employees created the demand, and the advancements in storage, sharing and computation created the ability of data socialization (Hans, 2017). Users wanted the ability “to search for, reuse, and share managed data” across the company (Joshi, 2017).

With the desire and advancements in mind, there are a couple reasons why data socialization works. First, it simplifies analytics creation for the everyday user. These everyday users are not as tech-savvy as those employed or educated primarily in a data, statistics or analytics heavy field. However, with data socialization platforms, they “can not only access this data and perform analytics, but also learn from their colleagues by sharing interesting resources or results” (Hans, 2017, para. 6).  Second, data socialization involves the idea of “the right data to the right person…at the right time” (Joshi, 2017, para. 10). The right person, a key player, can speed up the creation and distribution of insights in an organization (Hans, 2017, para. 6). This allows data and analysis to be used at every point in the decision making process, and thus makes the process more efficient and employees more productive (Marr, 2017).

Data socialization software can take different forms. One involves dedicated platforms for creating and sharing data and analyses. The second involves a set of multiple platforms that are tied together by an organization. In this situation, one platform might be used for data sharing and analyses, while another would be used for creation and storage (Hans, 2017).

There are advantages and disadvantages for both methods.

Having a dedicated platform makes the system user friendly. This means that creation, storage and sharing of data, analytics and insights can be done via a single platform. Dedicated systems allow for faster interaction between people and data. All-in-one platforms have a search function, allowing for all users to search to find data, charts and previously explored and created analytics and insights. Users can access all the information in one place, removing the need to login to different services. Dedicated platforms that use data socialization are created to pull extra information, such as “ratings, comments, and discussions” (Pannaman, 2017, para. 3). These platforms, however are more expensive than the other option (G2Crowd, n.d.).

On the other hand, combining services can be cheaper than dedicated platforms. This is because these services serve only one function (sharing, creating or sharing). For instance, Microsoft SharePoint is available at different price ranges, and is useful for different sized businesses (Microsoft, 2017). However, as the services are not streamlined, access to past and future data and analyses may be slowed. Methods that require manual data entry are also prone to human error, such as wrongly entered age, price or number of items (Developer, 2017).

The trend of data socialization will lead to improvements to understanding and speed in analytics. With access given to all users, employees can view previously made analytics and insights, enabling them to learn from past work. Easy accessibility also speeds up the review process and quickens the transfer of information from the creators/analysists to the decision makers. With access to data and analytics and ability to create analytics and insights given to all users, the task of analyzing data is broken down, speeding up the process for individuals.


Developer. (2017, March 4). How to Avoid Data Entry Mistakes. Retrieved from

G2Crowd. (n.d.). DataWatch. Retrieved on December 15, 2017 from

Hans, J. (2017, March 4). Crowdsourced Analytics: Using “Data Socialization” for Business Insights. Retrieved from

Joshi, N. (2017, May 18). Data Socialization: The Next Big Thing in Data Analytics. Retrieved from

Marr, B. (2017, Feb 28). Is Data Socialization The Next Big Thing In Data Analytics? Retrieved from

Microsoft. (2017). Compare SharePoint Online Options. Retrieved from

Pannaman, E. (2017, March 30). Beginners Guide To: Data Socialization. Retrieved from

Rouse, M. (2017, Feb). Data Democratization. WhatIs, Retrieved from

Sharma, S. (2017, July 26). Definitions and Models of Statistical Literacy: A Literature Review. Retrieved from