0. How to do data-driven marketing?
Hello, this is Hashscraper. Today's post is for small business owners, startups, and online marketing professionals who are struggling with online marketing.
Although marketing based on data is becoming mainstream.. many people are unsure of where and how to collect data, and how to apply it to their work.
If you are doing online marketing, you have probably had those concerns at least once.
So this time,
1. How to create marketing strategies using free big data services
2. How to collect SNS data and apply it to online marketing
I will explain these two topics with real examples.
1. Free big data services essential for creating online marketing strategies
There is a leading domestic service that allows you to analyze commercial areas based on big data.
It's Naver Smart Place.
1) Naver Smart Place
When you first start a business and do online marketing, the first thing is 'exposure'. It is essential to have your business name exposed on Naver.
At Naver Smart Place, you can check various perspectives of data. You can check the data of people who searched for your store (company).
You can check the data of potential customers through age group, time zone, gender data. If young women in their 20s and 30s search for your company name, you need to plan services and online marketing strategies tailored to them.
However, the type of customers who search and the actual customer base may differ. What if the search audience is in their 20s and 30s, but the actual customers are in their 40s and 50s?
If the information search results and visit (inflow) results are different, there is a problem somewhere. You need to find and solve that problem so that the search audience matches the inflow customers.
You can check reservations, orders, and reviews all in one app, which is very convenient. It has become essential for small business owners.
Most people tend to monitor only their own things, but the key point is to keep an eye on what the "competitors" are doing.
You need strategies to check the main menu/products of competitors, review popular reviews, and attract customers to your side.
It's even better to understand when customers mostly visit, where the inflow channels are, and the customer's flow.
If you list and analyze the above conditions, you will come up with a pricing strategy for products/services that your target customers will consume.
If you want to say "This crazy good restaurant is here," analyze the things mentioned earlier through Smart Place.
Isn't big data a big deal? Based on such data, planning products/services and doing online marketing is big data-based online marketing.
2) Naver Data Lab
It would be nice to know what trendy items or issues are for your target audience, right?
You can check such hot items or keywords in Data Lab.
Naver provides search trends and rising search keyword history, as well as search trends by shopping category.
You can also check real-time search terms and do keyword-based comparative analysis.
I compared the search volume of 'Pengsoo' and its competitor 'Pororo'.
Indeed, Pengsoo is the recent trend. The search volume has been increasing since mid-September, surpassing Pororo.
Pororo peaked on August 26, 2019. I looked into why it suddenly rose and found out that it was because a quiz about Pororo was featured on a popular TV show, which boosted it to the top of the search rankings.
75% of domestic consumers search on Naver, so Naver is the best for information and analysis related to Korea.
In addition, Data Lab has integrated data from various public institutions such as e-Nara Index and the Public Data Portal, making it very convenient. You don't have to search through numerous public data portals to find data.
3) Google Trends
This is only for Korea. If you want to know about exports or global trends, it is recommended to use 'Google Trends'.
As a global portal site, Google conducts big data analysis on search terms from around the world.
If you want to know how popular BTS is worldwide, you can search on Google Trends.
I knew that BTS was popular worldwide, but I didn't know it was popular even in Cote d'Ivoire, Africa.
Google Trends has been recognized for its significant analytical capabilities. It accurately predicted the election of US President Trump and Brexit in the UK through Google Trends' big data analysis. If you are considering exporting, it is useful to use Google Trends.
2. Collecting SNS data and applying it to online marketing
The SNS collection channel varies depending on your desired target and purpose.
If you are selling women's clothing for people in their 20s and 30s, you can collect data from Instagram, YouTube, and women's communities.
For marketers selling baby products for people in their 30s and 40s, you can obtain the desired data from baby cafes, Instagram, and baby product platforms.
If you want to evaluate the efficiency of online marketing, you can collect and analyze customer responses within the online marketing channels.
I will tell you how our customers collect and utilize data by channel.
1) Blog, Cafe Web Scraping
For blogs and cafes, you can collect everything visible on the web screen such as post titles, views, posting dates, post content, comments, and authors.
You can even collect from closed blogs or cafes that require login or membership, excluding posts suspected of being online marketing or advertisements. By collecting real data instead of ads, you can properly analyze the effectiveness of online marketing.
Recently, company B, which used a famous soccer player as a model for their ice cream, collected and analyzed blog and cafe posts to analyze customer responses to evaluate the online marketing effectiveness.
2) YouTube Web Scraping
For YouTube, you can collect more items.
You can collect video URLs, video titles, views, posting dates, likes/dislikes, subscribers, comments, reply comments, IDs, and more.
As the hottest channel, it is the best channel to analyze real-time responses before and after sales. However, there are not many places that analyze YouTube comments.
Why?! YouTube comments contain unstructured data and many sentences that require refinement, so the accuracy is lower. Therefore, it is a channel where you need to focus more on processing and analyzing the data rather than collecting it.
For a customer manufacturing smartphones, they collected and analyzed comments from major YouTubers to predict smartphone sales.
By analyzing the sentiment of comments from YouTubers promoting major competitors' products, they identified detailed needs for competitor products and used them as benchmarking elements to release similar concept products at lower prices, increasing sales.
3) Instagram Web Scraping - The most challenging but essential part of online marketing
There are no significant difficulties in collecting/analyzing data from most SNS channels, but Instagram is a challenging channel for data collection.
Those who have tried scraping will know. Instagram blocks IPs very well.
Do you know that Instagram provides a scraping API? However, there is a daily limit, so you cannot collect large amounts of data. Therefore, you have no choice but to use virtual IPs, but you still get blocked. Instagram developers are amazing!
In addition, there are many obstacles such as infinite scroll UX, changing class names, and more that make it difficult to easily scrape the desired data. Of course, our capable developers handle it well and collect data without any problems.
You can collect post URLs/images, follower count, following count, posts, posting dates, comments, IDs, likes, etc. from Instagram.
Many people analyze customer reactions in real-time by collecting and analyzing posts and comments of specific products or individuals.
Especially platform companies measure real-time product response and popularity to provide services that give customers information, so make good use of Instagram data.
By processing data collected from SNS through a series of processes such as data refinement, morphological analysis, and natural language processing, you can measure the positivity/negativity of each sentence.
Below is a screen showing the sentiment analysis of Instagram data collected by Hashscraper.
You can see scores in the sentiment analysis section, right? If it's close to 1, it's positive, and if it's close to -1, it's negative.
The analysis results showed an overall positive sentiment for the posts.
I showed you the analysis of posts for demonstration purposes, but you can also analyze comments.
Is my online marketing effective?
Does the positivity rate of Instagram comments affect product sales?
Is there a correlation between the number of site sign-ups and the quantity of positive blog comments?
If you have these questions in your mind, it's time to derive insights from data! (Please contact us)
So far, we have looked at how free big data services, SNS data, and online marketing practices are being used in real life.
Read this article as well:
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