Today is a digital age, with hundreds of thousands of gadgets at people’s disposal, including tablets, digital television, apps, smartphones, e-commerce, social networks and many more. A few years back, before the emergence of the digital revolution, the marketer’s work was to make captivating and catchy ads for television, print media and billboards. The digital age compelled marketers to evolve and to take advantage of technology in order to distribute messages. These days, marketers have a different kind of job, which include crunching numbers and statistics, gathering data, targeting individuals, deriving trends and finding the right channel among the many to reach out to the target clients. The digital age brought tons of data that marketers could leverage to make strategic marketing decisions via more accurate insights. Therefore, consumers served more useful content via ads.
MICROSOFT BIG DATA BOOSTS MARKETING CAMPAIGNS
A lot of organizations are leveraging data from different sources to boost their digital marketing campaigns. The campaigns were proven to be more effective compared to the old form of advertising. Taking the guesswork from the equation enables marketers to detect the changing trends and thus use them for more targeted marketing campaigns. The amount of data and sources is overwhelming, necessitating investment in bigger and more complex databases as well as data analytics tools to make sense of all the available information. Uncovering the insights results in the better ability of spotting opportunities, the right course and customer engagement.
KEY REASONS TO USE BIG DATA ANALYTICS TO IMRPOVE THE DIGITAL MARKETING CAMPAIGN
The following are key reasons to consider using big data to boost the digital marketing campaign.
✓Data visualization tools could help boost the effectiveness of campaigns. With the rise in competition, thanks to the digital age and opening of borders via the internet, marketers are finding ways to understand and interpret data fast. The data visualization tools are used for deriving actionable insight. For a business, these could include insights to flow of inventory throughout the year, lulls and peaks in shopping periods, and customer preferences and behaviors among others. Decisions are made based on the collective comprehension of data points, and gathering of various minds could lead to breakthroughs to considerably boost bottom lines, such as identifying slow-moving stock for better control of inventory, bigger savings and higher sales turnovers. Real-time consumer insights could help gain more customers and minimize churn. Analysis of consumer data with data analytics tools means that the marketing teams are better equipped to respond to consumer changes and demands.
✓Data analytics need not be expensive or complex. Aside from offering database management solutions, a lot of remote service providers now look to offer DaaS or data analytics as a service. This is ideal for smaller organizations that also have big data amounts but could not afford the cash outlay needed to purchase licenses and analytics tools. This could be done via remote service apps, enabling clients to leverage different analytical tools on their data to pay based on the processed data volumes. There are also interactive dashboards easier for non-tech savvy team members to get the insights from data store.
✓Using data on past events could help plan for the future. With a data-driven approach, marketers could analyze what is worked in the past so they could make better decisions moving forward. Backed by insights from consumers as well as other data forms, they could plan future campaigns and activities with a greater certainty degree. This is particularly important for businesses that need to questions their offerings often and tweak them to offer good customer experience. Say for instance restaurants could leverage insights from customer order information to determine trends and offer special prices on meals that are less popular. They could also find ways of improving products to make them more popular among customers.
BIG DATA SOURCES TO BOOST CAMPAIGN RESULTS
There are many data analytics sources that a business could use to boost the results of the next digital marketing campaign.
1. Web mining. This data is compiled through mining the web. It uses automated tools to uncover as well as extract information from web documents and web servers. Furthermore, it enables businesses to access structured and unstructured data from sever logs, browser activities, page content, site and link structure and other sources.
2. Social networks. Social media proliferated all over the world. The average internet user spends at least two and a half hours on social networks daily. Social networks enable marketers to harvest a huge range of data, from personal preferences to brand mentions as well as tastes via tracking posts, comments, shares, likes, check-in details and others.
3. Search data. This is data gathered from browser activity via using special tools for tracking search information and determine consumer intent and behavior. Also, consume5rs could be matched to their online persona via a method called onboarding. A business could then create a targeted online audience.
4. Transaction tracking. Each transaction run by or through a business provides useful data regarding users, whether it is financial, logistical or other related processes. Organizations could use transactions, such as purchases, insurance claims, withdrawals and deposits, orders and requests, booking and reservations as well as credit card transactions to have insight into the activities of the target audiences.
5. Crowdsourcing. This is a process of gathering public intelligence and has been made easier through the web. Big communities of people related by passion/interest are studied and the data gathered by running surveys and polls among other user-generate media.
Big data has such great power for digital marketing. Data analytics is one of the massive megatrends today, which continue to gain attention, together with the growing number of internet companies and users trying to convert the information into profits for customers. Companies that make extensive use of data analytics will witness a big profit improvement over the competition.