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MARKETING: The Use of Data Analytics in Marketing
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The Use of Data Analytics in Marketing

By John Feng

BT 201904 MARKETING 01在营销中使用数据分析

 

到目前为止,数据本身就是一个行业。有关消费者,企业或行业的可用信息量非常大。 正因如此,据Glassdoor称,美国数据分析师的平均工资为83,878美元/年,对于这样一个“新”行业来说这是相当多的。这个领域对大多数公司的重要性是不可否认的,但这些公司到底在寻找什么?

 

大多数情况下,他们正在寻求一种做出更好决策的方法。当您收集有关特定主题的数据时,您可以更好地最大化您希望的变量(销售额,利润,客户满足感,员工满足感等),这是合乎逻辑的。您不仅可以更加“确定”地预测某些外部行为,而且您不会对任何结果感到惊讶。您可以准备好以更好,更快的方式做出反应。

BT 201904 MARKETING 03By now, data is an industry by itself. The amount of information available about consumers, businesses or industries is overwhelming. Because of this, and according to Glassdoor, the average salary of a data analyst in the United States is 83,878$/year, which, for such a “new” industry, is quite a lot. The importance of this field for the majority of the companies across all industries is undeniable, but what are these companies really looking for?

 

Mostly, they are pursuing a way to make better decisions. As you gather data about a specific topic, it is logical that you will be in a better position to maximize the variable (sales, profits, customer happiness, staff happiness, etc.) that you are looking to maximize. Not only you will be able to predict with more “certainty” some external behaviours, but also you will not be surprised by any outcome, and you can be ready to react in a much better and faster way.

 

But in the specific case of Marketing, how does all this data really help us to make better decisions and improve our results? Well, it’s all about predictions!

 

Predict what your consumer will want and see yourself ready to sell it. Predict how the market will evolve and embrace new customers. Predict what the next big thing in information technology is and position yourself in it, and be the first to interact!

 

This all seems very promising, but how can you really achieve that level of prediction?!

BT 201904 MARKETING 02Customers

In a less predictive way, you should use data to profile your customers or consumers. On one hand, and as you can imagine, for big brands like WeChat or Facebook, it is quite easy to gather data, as it is simply “given” to them. On the other hand, in the case of smaller companies, there has to be a different approach, but still there are no excuses why they shouldn’t be separating their consumers in ways that suit their business.

 

If you own a pet store, for example, it does not make sense to advertise cat food to a person that only has dogs, right? This principle applies in any context from the minimarket owner, who can be aware of the client’s allergies, to the lawyers’ office that should target people who want a divorce in a different way from those wanting to get double citizenship. The good news is that nowadays, with technology, this is much easier to do and even an Excel sheet will help you a lot.

 

Besides this, data also allows you to assess why your customers are coming back to your store (or keep buying your service) or why they are going to your competitor instead.

 

In fact, the possibilities of scrutiny are endless and these are just some examples…

BT 201904 MARKETING 04Channels

With the use of data, it is also now possible to see which marketing tools are working for you, which channels give you the best results, and even in which of them your clients “like” you the most. This was unthinkable some years ago and nobody was really sure how effective any marketing campaign was. Now, through search engines or social media, you know in real time how your conversion rates are, your CTRs, or even your cost per lead. Even if in these cases it is not directly you collecting the data, you still have access to it through the several social or search platforms.

BT 201904 MARKETING 05Moreover, nowadays you can personalize your message to each of the “personas” that you identified for your business (if you followed the first point of this article, of course). Advertising to women over 60 years-old with an interest in traveling is as easy as targeting teenagers who love video games.

 

Sales

Among marketers, it is very common to talk about up-selling or cross-selling. In case you are not familiar with the term, allow me to put it in a very simple way – in an up-sale, your customers are buying something better than what they had planned, but also more expensive. In a cross sale, they are buying something that complements what they have already bought or are about to buy.

 

Now tell me, how do you think Amazon or Alibaba recommend you so many times products that you actually consider buying when you are looking for the perfect one or just after you made a purchase? Exactly, they use data to show you what others have bought that you should also buy, but also based on what you have bought before.

 

A very famous example of a cross sale was that men, aged between 30 and 40 years old, shopping between 5 and 7 pm on Fridays, specifically buying diapers, were also very likely to be buying beer. The grocery store that did the study, after finding this out, moved the beer aisle closer to the diaper aisle and the result… Well, sales of both products went up 35%! It looks as simple as magnificent, and all because of data analysis and the “magic of prediction”.

BT 201904 MARKETING 06Wrapping Up

Small or big companies, in Colombia or in Hong Kong, profitable or close to bankruptcy, need to deal with data. The number of customers does not need to be as big as Alibaba to make the use of data effective. Once you acknowledge the importance of all the information you can gather, you will be willing to make an effort to implement methods to analyse it in your company.

 

Don’t forget, get your hands on BIG numbers and you will have BIG results!

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