For this blog entry, find one quality article or white paper (from the past six months) that highlights a new trend or development related to data analytics. Create a blog post around the article and include the following:
- Provide the article title, link, and proper citation. Discuss the key topic covered and provide a high-level summary.
An article that highlights a new trend that relates to data analytics is 7 Digital Marketing Trends for 2021 and How You Can Prepare, which can be found here. The trend is real-time personalization, but it’s also referred to as just personalization. Essentially, it consists of leveraging data to tailor brand messages and content to the individual customer (Appier, 2021). Of course, machine learning, AI, and data analytics make it possible to do so. Also, as some may be aware, personalization has been the “talk” of the marketing world for years because everyone knows that consumers love personalized content. Delivering it, especially in real-time, can be quite challenging, though. But marketers can overcome this challenge by turning to social media analytics, website data, and other sources to mine customer data. By doing so, the user gets personalized content (i.e., an offer or promotion) based on what they are or have been searching for, which is a great way to nurture potential/existing customers and turn them into first-time or repeat buyers.
- Analyze the impact of the trend or development on data analytics.
Data analytic tools and techniques allow a company to take raw data and gain valuable insights from it (Jackson, 2016). This information typically consists of historical data and is useful for uncovering trends and measuring performance over time. But real-time data is needed to deliver the best customer experience, as their behavior can change quickly. And it’s not wise to create personalized experiences based solely on past information because many of the experiences consumers encounter will likely be irrelevant by the time they see them. With real-time customer experience analytics, though, a company can capture real-time patterns and behaviors and then offer relevant content at the right time to those users. Since we’re in the cold season, scarves will be used as an example of this. Essentially, a consumer may be searching for a scarf to complement their winter wardrobe via their favorite online stores to get the best deal possible. But they get distracted or step away from their phone or computer for a bit. And the next time they look up scarves, they’re now getting product listing ads that showcase various scarves and different deals (e.g. free shipping over $50) from popular brands. Hopefully, this allows you to understand how real-time personalization has improved data analytics and prevents consumers from having to spend countless hours scouring the web for the perfect product, like a scarf.
- State your position on the trend. Do you consider this trend positive or negative?
I consider this trend a positive, as it benefits both consumers and brands alike. More specifically, it gives people a more convenient way to shop that could save them time and money. And the businesses that have used real-time personalization have seen fantastic results, like a 26% improvement in brand perception, a 73% increase in engagement, and a 53% increase in their conversion rate (Dymond, 2017). And according to one study, brands that embrace this trend can outsell their competitors by more than 30% (Appier, 2021). That being said, now is the time to start implementing real-time personalization if you don’t want to get left behind by the competition.
Appier. (2021, January 5). 7 digital marketing trends for 2021 and how you can prepare. https://www.appier.com/blog/7-digital-marketing-trends-for-2021-and-how-you-can-prepare/
Dymond, D. (2017, January 7). Real time personalization explained. Net Elixir. https://www.netelixir.com/blog/real-time-personalization-explained/
Jackson, S. (2016). Cult of analytics (2nd ed.). Routledge. https://mbsdirect.vitalsource.com/#/books/9781317561880/cfi/6/30!/4/226/2@0:38.2