Future Of Data-Driven Marketing
Data is the sole ingredient in all digital processes today. From the first online shop by NetMarket or Internet Shopping Network in 1994 to the Amazon online of today, data in marketing has increased over the years.
77% of the running companies have content marketing strategies in place, whereas 40% of the total marketers consider it as very important. If we consider email marketing, social media marketing, video marketing, or other modes of lead generation, then the number increases to a significant level. So, what is its future? Let us discuss this in detail.
A Long-Standing Practice
If you think about it, taking business decisions based on available data isn’t some new concept. You must all have observed that in your local grocery shop, the things that wouldn’t sell wouldn’t be available anymore, and the store would keep the popular items in stock more.
All the previous marketing decisions were based on the observation and measurement of a principle parameter; however, you can also get insight with the analytical tools and a wide range of data in the modern world. This triage of scalable data collection, analysis, and implementation of the results has made the job of making data driven marketing decisions more manageable and exciting.
How Does Insight Into Marketing Trends Help?
Insight in marketing is now vital, as it helps pinpoint the preferences and the demographic need to be targeted. The old approach of “shotgun marketing” is not relevant anymore. In detail, the problems with traditional marketing had been two-fold:
The lack of information and methods to have a pinpoint focus and offer personalized experiences.
The inability to feature marketing influence across all channels and emphasize the right metrics.
Data driven marketing tools provide the marketers with future-enabled insights from historical data, which saves them time, effort, and money. With the correct data, marketing professionals can predict the customer preference, identify the responding customer profiles, determine what strategy is the most responsive, and even when the customers are most active. All of these factors make the current marketing campaign optimally focused than older product promotions.
Moreover, data-driven marketing helps select the right approach that reaches the intended user, at the correct time, with the right message, ultimately causing an action to generate a sale. For that, the marketers will need to invest in analytics.
Why Is Analytics Needed At All?
The most straightforward answer is the sheer data volume and the understanding to interpret the data found. Trusted sources report that 54% of business data is generated internally, 25% is obtained from external sources, and 21% comes from combining the two.
It is prevalent to get lost in the torrent of data coming in your way. However, they also cannot be expected to become an expert overnight. That is why the future of data driven marketing for the companies will depend on the investment in the required tools, technologies, and talent to understand the complexities of data analysis and create effective data-driven marketing campaigns.
Different From Web Analytics
Although marketing campaigns sometimes need to optimize the traffic visiting a business website, web analytics is a little different from data-driven marketing analytics. Web analytics is concerned with the SEO, site speed, and other components of the performance of a business website for client engagement and conversion.
On the other hand, marketing analytics is mainly involved with collecting and interpreting marketing data from various sources, finding the connection and correlations within the datasets, and identifying the configurations and trends for further implementation.
The Types Of Marketing Analytic Tools
Discussion on the future of data-driven marketing will need a better understanding of the analytic tools used in interpreting the data. In the current situation, data driven marketing analytics is a priority for marketers – 40% of them are increasing the allotted budgets, and 64% of them report that strategies designed from marketing data are helpful in today’s economy. Relatedly, the following analytic tools are used in the current marketing industry:
- Text analysis
- Statistical analysis
- Descriptive analytics
- Diagnostic analysis
- Predictive analysis
- Prescriptive analysis
- Competitive landscape analysis
Also known as text mining, this method uses complex computer programs and data mining algorithms to extract patterns from large data sets. This data enables marketers to learn more about their customers to create more effective marketing strategies.
The principle of finding patterns in the data remains the same here. Statistical analysis is applied to collect, analyze, interpret, present, and model the available data. It also highlights the critical points of past strategies by effective data visualization like dashboards.
This analysis method applies data aggregation methods and data mining to provide marketers with a glimpse into the past developments and analyze the details of what happened then. It can be defined as a way to link the market to extract the information required to make quality decisions. Market researchers use this method to perform quantitative market research and calculate specific parameters like average and percentage for summarizing detailed data.
Opposite to the mechanism of action of descriptive analytics, diagnostic analytics answers the “why has it occurred” question than “what has happened?” it is more related to finding the underlying cause and processes instead of the result.
Predictive analytics is performed using statistics and modeling techniques which give the marketer information about the future performance. It is essentially answering the question, “what could happen in the future?” Data driven marketing with artificial intelligence is an extension of this analytics. It also uses statistical models and established forecasting techniques to complete data analysis from data sources with predictive value like Email responses, webinar attendance, event participation, opens, website visits, engagement, etc.
This data analysis technique works by advising on the probable results by applying a mixture of methods and tools such as trade guidelines, algorithms, machine learning, and conceptual modeling procedures. The marketers find inputs from a variety of cleaned data from various sources. The information could be historical and transactional data, Big Data or real-time data feeds. The marketers use this analysis primarily by utilizing optimization and simulation algorithms to get information about the possible outcomes. Essentially, they try to find an answer to the question, “what should be the plan of action in the future?”
Predictive analytics is helping b2b data driven marketing attributions more accurately by applying cutting-edge algorithms and more advanced attribution models. The techniques allow them to determine the actual cause of conversions and better understand future planning and actions.
A competitive landscape analysis measures how your business relates to comparable firms in a competitive situation, also called competitor research. A competitive landscape analysis usually includes examining the companies’ marketing strengths and weaknesses compared to their competitors.
The parameters may include but are not limited to sales numbers, brand acknowledgment, or strategic components of marketing, like website traffic sources and analytical breakdown of your competitors’ advertisements. This analytical technique helps the professionals learn and define their data driven marketing strategy from the differences with their opponents’ tactics.
Marketing research and analytics take a long time if performed manually. Several data-driven marketing tools are available now that make tracking the competitors’ performance across social media channels. This approach saves time for the marketing professionals to concentrate more on the tactical aspects of their profession.
Subsequent Actions After The Marketing Campaign
After the termination of a marketing campaign comes the comparing and analysis of the ROI. The results form a fundamental part of future campaigns. After the research of the competitive setting is finished, the marketers analyze the data to gain in-depth insights from the campaign results. It is more beneficial to employ tracking algorithms in real-time for marketing professionals. The approach enables them to make informed marketing strategy decisions that leave a positive impact on future campaigns.
Data-driven marketing analytics provides a marketer relevant information about their competitors, their novel sellable characteristic, and a verifiable insight on their ideal customers. These data provide them with a platform to establish future campaigns constructed on solid data then guesswork. Data-driven campaigns are more inclined to choose the correct marketing channels, target the appropriate customers with the right approach, and ultimately translate into a better return on investment.
Balancing The Pros And Cons
The global digital marketing space will increase by about $100 billion over five years. The factors behind this drive are several Big Data initiatives, namely, paid-search internet, mobile internet, display internet, and classified internet. Relatedly, data-driven analytics is becoming the most crucial factor in making important marketing strategy decisions. For this reason, an increasing number of marketing professionals are investing more money on data driven marketing platforms.
Marketers mainly use the following techniques to gain insight into consumer behavior, such as customization, location-based targeting, and mobile and real-time reporting. There are several advantages of data-driven marketing:
Increased customer satisfaction and preservation.
Improved extraction and acquisition of information.
On the other hand, technological problems, the ability of the users to interpret and utilize big data correctly, and data verification and validation challenges remain points of concern. With the continued and evolving facet of data driven online marketing, future marketers have to find the optimum balance for their campaigns.
Marketers can derive these advantages of data-driven marketing with the help of comprehensive brand analytic solutions such as the one offered by Wersel Data-Hub. Adopting the solution will offer you an unmatched competitive edge and unlock opportunities with the help of data from online marketing.