Processing a large amount of data using Big Data is the way to increase sales
By analyzing information about customers and purchases made on the site, you can be aware of the characteristics of users, which will make it possible to offer what is needed in time. By personalizing the resource as much as possible, you can achieve the highest conversion and withstand high competition.
What information can be collected using Big Data?
The information that is collected on the site is divided into two parts: about purchases made and about customers.
Information about visits and purchases
| Information | How you can use information to sell |
|---|---|
| Purchase history (what, when and how much was ordered; frequency of purchases; use of promotional coupons; product price) | You can offer similar products at the right time in the same price range, talk about discounts and promotions via SMS, newsletters, information on the site |
| Purchases via mobile phone | Customize your site's mobile app for a bigger and better customer experience |
| User behavior on the site: what did you like / dislike when choosing; on which pages he was longer than usual, and which ones he left quickly; which products have been viewed, which have been added to the shopping cart; at what stage of the purchase did the resource leave | Set up the possibility of offering a specific product/content to a specific client that he liked; personalize message forms, alerts and product recommendations |
| What site did the person come from? | Identify the least and most effective advertising channels; use the most efficient |
Use of services (such as "Callback", "Online consultation") | In time, offer the client the service they have chosen earlier |
Client information
| Information | How you can use information to sell |
|---|---|
| Goetargeting | Customize the display of content and catalogs depending on the region; geotargeting of service and advertising messages |
| Demographics (age, gender, interests), marital status and possible presence of children, profession, ownership of movable/real property | Create unique offers for each client, starting from his data from questionnaires (including for birthdays and professional holidays); personalize product recommendations |
| How a user behaves online: social media presence, groups/communities, circles | Look for a new similar audience where your client happens to be (of course, we mean sites), among his friends, acquaintances |
Personality type, how he perceives information | Submit information individually; customize the service for each client |
Methods for processing information sources
The web resource itself is the main source of the necessary information about the client. The information left during registration, in questionnaires, reviews and surveys - these are the data that almost every online store collects. Analytics services from Google and Yandex make it possible to collect all the necessary information: site traffic, visit routes, popular sections, user behavior and the depth of its routes. Social networks, blogs, forums, mobile applications and information providers from outside (customer base sellers) are definitely useful sources of data.
Modern technologies make it possible to automatically absorb and process huge unstructured volumes of information. To your attention the main Big Data solutions:
- Database management systems (Microsoft, IBM, Oracle, Sap). Store and process information. They also analyze the movement of indicators and provide the result in statistical reports. Based on this data, the systems conduct predictive analytics and issue conclusions with recommendations (for example, how effective is the advertising campaign, how the number of orders will change).
- Algorithms that analyze Big Data and extract useful data (intentions, interests, preferences). Algorithms form predictive models in order to prepare marketing campaigns and provide information on the most relevant advertising methods.
- Tools to help personalize RK:
Buyers of RTB-advertising. Predict user actions, target ads across all channels.
Product recommendation tools. Shows on the site the product that is most likely to interest the client.
Personalizing content. Show the most appropriate version of the pages.
Targeted advertising tools in social networks. They help in attracting potential customers and increase conversion. They also help to reach the target audience as much as possible, announce new products and promotions, and improve the company's image.
All of the above tools, as a rule, interact with each other. In addition, they are constantly improving, expanding functionality. Startups that work with Big Data are also constantly appearing.
As an example, SocialKey Ads is a social media ad targeting system. Here's another one: Persuasion API is a service that relies on the psychology of persuasion to personalize a resource.
Effective use of Big Data
Conversion rate optimization needs to be done constantly. Otherwise, the site will not survive in the sea of competition. A personalized resource is always a few steps closer to its client, on the same wavelength with him, so to speak. For example, a person received a newsletter, after which he went to the site, looked at something specific, but did not buy anything. Send him the same item at a discount in the next mailing list. By analyzing site visits and carrying out competent further work, you can improve behavioral metrics, adapt the site to the client as much as possible, thereby contributing to improving the position of the resource in the search results.
By analyzing the activity of the user, his friends, and the community, you will discover new sources of audience. In addition, new advertising channels will be found. If you know, for example, what gadget a client uses, you can create services and applications that are likely to be of interest to him. If a person mainly uses a phone to order, it will be useful for him to know that you offer to download a mobile application for ordering via phone, and similar goodies.
How to use a large amount of data? There is simply no single pattern. An important factor here is the willingness of the company to invest and innovate in business development. Large companies working with large volumes of information can afford to allocate experts to work in this direction. Ready-made services do not require additional costs. They are quite easy to implement in the work of the resource. Such services enable small companies or those who do not have additional funding for Big Data to work with a large flow of information.
Remember that the information you process is very important. Learn to filter and discard the unnecessary. Thoughtless processing of the entire stream is a waste of time and money. For example, a website that sells TVs doesn't need to know if you have a pet. The correct setting of tasks and goals for services that process big data is the key to your success.