Marketing in the present times is mostly data-driven and this makes data a cornerstone of the marketing arena. But this dependence on data has also made it essential that we have a clear and bigger picture of the data to achieve great results.
Marketing in the present times is mostly data-driven and this makes data a cornerstone of the marketing arena. But this dependence on data has also made it essential that we have a clear and bigger picture of the data to achieve great results. This is where data enrichment comes into play.
Data enrichment helps one to arrive at a panoramic view of data. It is the enrichment of the data by merging third party data from external sources. The external sources could be anything from social media accounts to mobile devices.
Enriching data is an essential for marketing as it’s a step that takes one closer to their customer—by providing a deeper awareness of who they are and what they are seeking. While this happens, it is also important to ensure that the external data is reliable, authentic and sufficient. Once these checkboxes are marked, the bigger picture provided by the enriched data becomes a multidimensional image of the customer, where one has all their required information. This will drive the campaign in the positive direction along with progress in customer experience and personalization, growth and better lead conversion.
Also known as ‘clustering’, segmentation is the grouping of customers into segments based on shared qualities and characteristics. These segments can be based on a wide variety of factors such as age, income, demography, behaviour, geography, and customer journey. This helps in gaining insights into the marketing landscape as well as to reach customers who were previously inaccessible.
Manual lead scoring being a tedious process has given way to automated lead scoring, where the marketing system assigns numerical values to the customers, scoring each of their interactions with the company. These scores are then weighted based on the expected value. For this to work out efficiently, a model that accurately scores the inbound leads is essential. The automated lead scores help in understanding the engagement levels of the leads, thereby filtering out the leads that are qualified enough to be passed on to sales.
Lead generation forms play a key role in churning out first hand data of potential customers. As important as the forms are, it is more effective to keep these forms as short as possible. This is because there is a high chance of a potential customer turning away due to the evasive and lengthy nature of the forms. On the other hand, a crisp form that asks for only the relevant and necessary information builds a better customer experience. With the help of data enrichment, other additional information can be collected in real time to analyse the quality of each lead.
The database of the existing customers is of high value. Through good quality data, it is possible to expand the market, by recognising existing customers who might want to try other services or offers of the brand. Data enrichment gives the data the opportunity to expand and grow in quantity, which leads to increase in revenue.
Customer conversation with artificial intelligence machines is a relatively new way of procuring data. A friendly and helpful chat bot can extract information in the form of conversation that one might not receive through any other form of customer interaction. The data acquired from these conversations can then be enriched with the existing information from their database or from third party data. This method encourages growth in customer base as well as in retaining customers.
By boosting the value of data assets by constantly improving and updating them, data enrichment nudges the company to generate strategies and decisions that are suitable for the company. Data enrichment makes the marketing soil more fertile, by adding all essential and accurate information. Our data is tested and real-time, and accuracy is our prime quality at infoAnalytica.
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