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How to Improve Your Leads with Data Aggregation?

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Business and economics are all about strategic allocation of limited resources. The main resources of humans are time and energy. There are many things requiring of both in our daily business operations. Among the most important of them is data analysis. Today, the ability to make decisions based on big data is increasingly important. But how do we manage it with our limited resources when there is so much data out there? One of the most helpful processes in this situation is data aggregation. By summarizing large amounts of data, it allows improving many pivotal business processes, including lead generation.

Concentrated information

The same thing can be said in many different ways. Similarly, there is more than one way to present the same information. For example, if you are wondering how many billionaires there are in your country, you can make a list of all of them, or you can just note down the number. Statistically what will matter in most cases are the numbers – sum totals, percentages, and such. This is what the process of data aggregation takes advantage of. It merges information from various databases to provide it in concentrated form. The summaries of relevant data are more accessible and readily usable for important insights and business strategies.

Data aggregation is usually done by software programs made specifically for this purpose known as data aggregators.  This is due to the fact that although manual data aggregation is possible, it takes a lot more time and has a higher risk of errors. As saving time is one of the main benefits of data aggregation, doing it manually sort of defeats the purpose.

Improved leads

Utilizing the process of data aggregation has many benefits for businesses. Generally, it allows reaching strategical business decisions based on large amounts of data in a reasonable time. But the advantages of this process can also be seen in many different areas of doing business. To illustrate this point, let us look at some ways that data aggregation assists in improving the quality of leads.

1) Marketing campaign analysis

In order to improve your lead conversation rates, you need to constantly review all aspects of your marketing to see what works and what does not. Data aggregation helps to do that by collecting and digesting the information on the traffic on your marketing platforms. The summary of how potential customers react to particular marketing actions and initiatives will show the strengths and weaknesses of your campaign. This will allow you to see what needs to be improved and make well-informed decisions on how to amend the campaign. The upgraded campaign is sure to generate higher-quality leads.

2) Getting more high-quality leads

More does not necessarily mean better. But when you get to know where to get something good, naturally, it makes sense to try and get more of it. Aggregating data from various sources will show where the good leads are coming from. This will allow dropping the lead sources that do not pay off and concentrate on acquiring the leads from the right places. Getting more leads from high-quality sources will lead to improved lead quality and higher conversion rates.

3) Seeing hidden opportunities

One of the main advantages of data aggregation is the ability to discover unseen and unusual patterns. As through this process, a lot of information is presented in an accessible form, it provides an opportunity to see what would otherwise be lost in the jungle of data. This means that new opportunities for marketing campaigns and lead generation can be uncovered. Analyzing the aggregated data will allow exploiting these opportunities by creating novel marketing strategies and getting great leads in previously hidden ways.

Different ways of data aggregation

Leads are essential to any business that is trying to find new customers and grow. The way data aggregation improves lead quality is alone a good enough reason to harness the power of this process. Of course, there are many more advantages of data aggregation that make it clear that one has to utilize this process for success.

But how do you do it? There are many features that distinguish different methods of data aggregation. For example, data can be aggregated from a single resource or a group of resources and over different periods of time.

However, the most important distinction in data aggregation is between automated and manual. As mentioned, manual aggregation usually does not pay off. It can be applied in certain circumstances when the amount of data is manageable and there is time enough to go over it manually. Usually, however, we have too much data and too many important ways to spend our time. In this case, we would use APIs and data aggregators to do the job and dedicate ourselves to analysis and decision-making.

Source: Tom Wilson / CoreSignal

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