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9 Highly Useful Data Segmentation Tips For Meaningful Web Analytics

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Web analytics is required by the businesses for the data analysis and improving the business in the long run. It is used by all the online businesses that wish to understand their customers and learn more about them on a regular basis. The analytics tool help the businesses understand the true source of the traffic that is coming in which can be segmented and then analysed by the field experts. The conversion funnel can be studied well with the help of web analytics. There is no one good metric that can be employed to gain all the information about the business or there is no possibility of creating a dashboard which is sufficient in itself.

This blog discusses 9 web analytics tips for the proper segmentation of the data and convert it into meaningful information.

1) Follow the sequence of segmentation

The sequence of segmentation is simple with the first step being filtering the data, the second being grouping the data and lastly the segmentation. The volume of the data is generally huge which firstly poses the problem in managing it rightly and then understanding it. You can move beyond ‘top 10 or 20’ list which do not alter greatly over time before segmenting the data by grouping the same.

2) Find out the segments of the visitor type

Find out whether a new visitor is in the category of a customer or an affiliate, a prospect or an employee. The online behaviour of the visitors depends on their category and it is necessary to understand each one of them separately. The visitors who are employees may not contribute much in the sales of the products or the services and hence may disturb the data collection.

3) Identify the traffic source and segment accordingly

This involves organic versus paid search, external and internal display advertising, affiliates and social media that is owned versus earned. There are many web analytics solutions available in the market that can give basic segregation of reports on traffic source but if there is a need to move beyond the 3 basic types, additional tagging would be good idea. The social media that is earned from sharing of the content is an important one to be considered along with additional tagging in the process. The other segments to be taken into consideration are the social media that is owned which includes the Facebook or YouTube channel of the company, organic search versus paid, internal versus organic (link building) referring domains.

4) Check direct traffic

Direct traffic must be segmented properly and hence, there is a need to tag the sources of the traffic that is generated from the social media platforms, emails or is redirected from the various platforms. The traffic obtained from the mobile devices using the QR codes must be tagged properly with the help of query string parameters.

5) Content categorisation

This involves purchase, research, transact, renew and recommend not in this sequence though. Content for an email is generally written for different personas that are to be targeted. One can optimally use the same nomenclature for content targeting for the purpose of understanding the web analytics data reports. Over a period of time, one will find it easy to leverage the user experience in order to funnel all the visitors. This can be achieved through sales process that is completely logical and starts from the basic step of research and then purchase which leads to transaction or renewal and finally to the well desired stage of recommendations. The content must be segmented according to the intention.

6) Club the data sources on various platforms

The behavioural data for web analytics should not be replaced with the transactional data of the business. There is a need to club the data sources in order to understand the differences between the data related to accounts and the one meant for analytics.

7) Be customer specific

While implementing any strategy involving web analytics, it is required to pay attention to scientific or technical nomenclature that hinders the clear understanding of the data obtained. There is no place for the jargons to be included in the final reporting of the web analytics data which are not easily understood by the business persons.

8) Set reasonable targets

A web analyst is categorised as good if he is able to successfully predict the market trends in the long run based on the hypothesis obtained from the data. An intelligent web analyst will then try to make the analysis much easier by including the guessed estimates in the future analysis of the data in the coming months, quarters or years.

9) Integrate the metrics and segments with key business drivers

Web analytics can be used to focus around the acquisition of the important products by simply segmenting the data accordingly. The data obtained will be useful in product designing in the future. There is no harm in highlighting the customer segments of prospects and new customers. Integrating it with the business implies that proper attention must be given to detail and the audience must be positive about the analysis and be open to required changes.

Web analytics is something that is indispensable for the businesses that have a goal chartered out for themselves. It acts as a signpost for the driver to follow and take the necessary turns in the implementation of the business marketing strategy. The data shows all the important aspects of any business activity which is segregated into several categories for better understanding and good results. If you are 100% committed in earning more revenue for the business this year, then it is required to understand the above mentioned tips thoroughly. The tips are not for the experts but anyone who is interested to improve the score on the revenue sheet this year. One tip followed at a time is a good idea to move in a safe and fruitful manner and it is not necessary to push oneself to understand each and every tip right away and get confused. Slow and steady wins the race!

  • web-analytics

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