With over 13 years of experience, Keelia has a deep knowledge of client challenges, is passionate about customizing solutions to best fit their needs and helping them exceed their business goals. She is an expert in location analytics, ad tech and digital marketing. In her free time, she enjoys spending time with her daughter, doggos, and friends as well as listening to podcasts and reading.
Here are four specific areas where a location analytics product is particularly helpful:
A lot of times location analytics companies are looking to expand the data they offer to provide better coverage to their clients, while also making sure that the information is as up-to-date as possible. The ability to expand data attributes, ensure data accuracy and completeness as well as the option to get real-time updates are critical considerations when evaluating a data source. For example, location analytics companies can leverage consumer transaction data to understand how a particular zip code indexes against the whole city. Alternatively, they can access high-quality business data to understand a business’ employee size, industry, and site location (physical address) of competitors in a given area.
When it comes to analyzing businesses, everything from employee size, sales volume, SIC/NACIS or industry, location linkages, and more is often leveraged. When it comes to analyzing consumers, local analytics companies might be more interested in age, household income, children present, spending habits, and more.
This data can be implemented in a variety of formats and is often customizable depending on the client’s needs. Whether they want to manage a full file, make real-time API calls, or a combination of the two, the data delivery can be flexible
When it comes to local analytics, companies should look for these four things when selecting a data partner:
a. Data Quality – where is the data sourced from? How is the data validated? what quality checks are in place for the data?
b. Data Accuracy – how often is the data updated? Do you have access to data that is being updated in real-time? How is the data maintained over time?
c. Data Coverage – what is the coverage of the data? How do you manage chains and franchises? What types of linkage do you maintain? Do you have sales volume and employee size on business locations?
d. Data Delivery – how is the data being delivered? Can you inject data and perform key processing directly in your own platforms as you need it?
Interested in learning more? Download our whitepaper, “5 key elements for building a successful data-driven product,” or contact us to learn more about how to put data into action to build a better product.