In India, most marketing managers and executives lack the necessary data, which, when combined with their inadequate data analysis, paints a picture of how marketers are ill-equipped to drive big data analytics. They’re having trouble developing a unique approach for customers across all channels in a timely manner.
People talk about individualised customer experiences, but they require good data about customers, their behaviour, channels, and so on to create them. Numerous studies have shown that enhancing data quality is the most important issue.
Big data will undoubtedly be quite beneficial to marketers. Most businesses, however, do not delve farther into it for a variety of reasons. Big data analytics is still a buzzword for most small and medium businesses (SMEs).
They primarily analyse to evaluate campaigns, media channels, and results, but they do not devote significant resources to predictive analysis prior to the launch of a campaign or to designing a campaign based on it.
We now have sufficient instruments to analyse digital media and website-related information. For example, Google Analytics is a widely utilised tool. There are numerous software options as well. We can track the success of anything digital, including webinars, live videos, events, mail campaigns, and chats. We can also track our consumers’ online interactions.
Leading marketers analyse the sales cycle from the time a potential customer first interacts with your website or social media site until the time they purchase your product or service, as I’ve mentioned in many past columns.
Statistical methods enable us to match the positioning of our campaign to the desired consumer profile. With almost precise tailored mailing, we may also reach the customer directly.
Business intelligence technologies can help you consistently find the ideal buyers and convert them into customers. This type of big data analysis aids in establishing a real-time connection with customers as well as uncovering prospective new prospects for improving performance.
Improved alignment with sales, better consumer experiences in the digital and physical worlds, and, of course, a better eco-system can all help marketers show a greater return on marketing investments (ROMI).
How to optimize the data
Most marketers, however, have not delved farther into this sector due to a variety of misconceptions about big data.
Many marketers, for example, believe that gathering data is all they need to do. It is critical to collect the correct data, but this is simply the first step. Working with data to boost consumer reach and engagement, as well as converting leads and convincing them to buy, is more important.
The analytics should evaluate all other associated data and provide you with a report on the performance of all media operations. It should also assist you in analysing customer behaviour and making real-time changes to your messaging or offering.
Many marketers feel that all they need is technology to make big data work for them, but human involvement is necessary. Today, we all employ a variety of technology in our marketing strategies, but the ability and abilities to use them effectively are more vital.
Your staff must be able to comprehend the various outputs of these software tools. For accurate measurements, etc., the most recent versions of the tools should be included and coded immediately into your website. All of this is done to guarantee that multiple data sources are combined to form a wider picture.
Multiple sorts of data can help you determine which sections of your business are performing well and which require additional attention. Also, make sure the team has a skilled techie on board who can conduct the analytics and is comfortable with the setup and real-time testing. This resource must have strategic thinking skills, technology understanding, and an analytical attitude in addition to marketing expertise.
Many marketers also believe that they simply need to conduct analytics once and then use the results indefinitely. This isn’t going to work. We require a dynamic quality data analysis system that captures real-time changes and enhances predictability. Scores fluctuate rapidly, and if we don’t account for this, our planning will be wrong.
Finally, marketers make the mistake of believing that the more data they analyse, the more value they will derive. Isn’t this at odds with big data? Not in the least.
There is no such thing as too much data. The quality is very crucial. A large number of data points will finally reveal the fewest ties to reality. For example, if you notice that customers with names beginning with P buy more frequently from your store, but you don’t offer any forecasts to boost sales, that’s a warning flag. The goal is to strike the correct balance between your company’s needs and the data points available.
Marketers may enhance client equity and revenue by correctly utilising big data analytics.