Online Research Services To Fix Marketing Flaws

by Beverly McNally I love to read and write about technology such as

Do you know the pace of Amazon’s growth? It’s exponential. Since 2009, it has grabbed half of the US market. Isn’t it amazing!

How is its growth rate accelerating-do you know it?

Well, it’s the wonder of online research services that takes all credits. Yeah! 

Its access to a pool of the customer’s knowledge is incredible. It knows what you and I search online. It’s what we call the generic search. Around 70 percent of the word searches on Amazon’s search browser are the finest example of this saying. They are all generic searches. Online research services help it to understand what they are. Let’s say, you search men’s backpack rather than Wildcraft or Aristocrat backpacks. 

So! How does it happen?  How does it push other competitors and gain a leading position?

Well! This is an outcome of crunching big data smartly & thoughtfully. The digital marketing landscape is expanding rapidly. Likewise, its exploitation is on a high rise for big data analytics. No business is invulnerable to this fact. But, every business is unable to filter out the best decisions out of large datasets. New Vantage Partners’ Big Data Executive Survey (2017) has revealed that only 37% companies are successful in deriving profitable decisions. 

Have a look below how online data research makes it possible:              

Data capturing to translate shoppers into buyers:

You need data to catch the fruitful insight. Fortunately, you have a dozen of sources to access your customer’s data. Your customers take several paths, like feeds, reviews and peer-to-peer networks to pay online. Although it’s not-so-easy to abuse all of them, yet the marketers are blessed with advanced tools. Google Alerts, keyword planners and Google Analytics have made their jobs easier.    

Besides, POS system (let’s say) offers a direct vulnerability to customers’ intentions to their conversion. That’s why Walmart has acquired a part of Flipkart this year. It vividly depicts very effective concept of online to offline customer experience. For any organization, an in-depth knowledge of different points on the customer’s journey, their experience and impact points are essential to capture their data. The organizations, like Amazon, Walmart, Flipkart and many others, stick to these points while capturing data:

·         Access various touch points from where the customers visit

·         Set up a schedule to take appropriate action, like when to pitch.

·         Determine the sentiments of the customers and pitch at that point, like festive occasions.

·         Identify the customer’s behavior and their shopping patterns.

Data scrapping to filtration: 

·       Data is overwhelming:

The data from IDC states that the digital universe gets double of its present size in every two years. By 2020, the data size will reach to 44 zettabytes   or 44 trillion gigabytes.

Now, can you imagine how much data one organization can have if it exploits its IoT (Internet of Things, like camera, sensors and so on) only? And, their size expands day by day. It’s likely to be extremely hard to scrape the useful chunks out of that gigantic data cluster. Anyhow, if it thinks about sifting through that data, determining the profitable patterns is an uphill battle.

·       Data scraping:

Therefore, consider narrowing down the sources of your data. Extract that data which actually pay you off in terms of the revenue. Let’s say, you need to identify the managers of the Hotel industry. Focus on the LinkedIn data. Filter out the profile of the hoteliers and their staff.

·       Filter to catch value:

You don’t need to have other details of a particular hotel, like number of employees, names and email ids of CEO, assistant managers and others. Just target what matches to your ultimate goal, i.e. the managers (as considered as an example above). These kinds of relevant details will save your time, money and efforts. Eventually, what you get will be the exact data that you can harness for deriving valuable patterns.   

Critical analysis: 

·        Know the goal:

It’s a crucial step. You should have a crystal clear image of what you want to achieve. Let’s say, you want to target the existing audience only on your eStorefront. So, you have to filter out their data. Identify their wants. Target them with the lucrative strategies accordingly.

Amazon does it with expertise. It allows a new retailer or manufacturer to sell in small quantum. Simultaneously, it scans its sale’s figure. Finally, it places orders in bulk if the customer’s satisfaction level is satisfactory. 

·         Identify metrics:

So! What’s the plan? How can you accomplish your goal? If you reconsider the aforementioned example, you need to attend the bounce rate. Also, look into the feedbacks and the interval between the product reviews and payment.

You can try an experimental approach. Like Amazon, you can crash price on their preferences. Keep it momentary. If it ends up at sale, carry on with this approach.

·         How to aim at:

As suggested above, you can derive a plan according to the driven analysis of the customer’s behaviour. If the browsing ends up on sale when you drop down prices on their preferred items, your strategy will prove game-changing. Define your own threshold according to the online searches.

Data privacy: 

Privacy is a major concern. It can’t be ignored. If you deal overseas online, be attentive to the GDPR (a data privacy regulation).  Provide with complete privacy to the data subject. The searches and sales data can be vulnerable to you. But, its use is a subject matter of privacy.

However, this regulation doesn’t impact Asian trade. But, it’s the best trade to bet on if you assure privacy to the data subjects. Maintain transparency while collecting personal information.

These online research services can prove the best hacks to fix your problem of less number of sales.

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Created on Jul 31st 2018 04:07. Viewed 362 times.

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