In the online advertising world, advertisers use their budgets wisely by presenting their ads to a specific audience most likely to be interested in the advertised products or services. This “targeted advertising” increases the probability of converting ad impressions to actual sales and is the norm in online advertising.
Small and medium sized businesses typically allocate budget for offline advertising as well. Whether in the form of paper flyers distributed in shopping areas, billboards located in specific neighborhoods or digital signage placed in public places, it always makes economic sense to select locations which are likely to produce the highest impact from the advertising campaign. This is targeting the campaign to a specific geographical area, rather than randomly distributing out-of-home advertisements and wasting excess budgets.
The challenge in both cases however, is how to best define who the existing and potential customers are so that a focused campaign can be planned?
Breaking down customer data
Data concerning product purchases is collected from an enterprise’s financial systems, information about existing customers is provided from the CRM or a loyalty card membership system, and potential customer segmentation is derived out of market reports or surveys. Based on this data, a description of customer types becomes clearer, including some understanding about what drives purchase decisions.
In the online advertising case, a potential customer is also identified by his/her individual preferences based on historical online searches on a specific website or through search engines. This is typically used to map the customer to a predefined type in order to place suitable product/service on the specific page being viewed online.
Conversely, offline advertising typically addresses a group of anonymous people who are located in the same geographical location, whether it’s a crowd passing in front of a certain area or a specific residential neighborhood. In some cases, offline advertising may address a population with something else in common, for example, children who study in a nearby school or employees of a financial commercial district.
This lead to our team’s observation that understanding the movement patterns of crowd can provide high value to the planning of campaigns. In Nokia, we took advantage of those learnings and created Nokia Crowd Analytics. It is however, not a current practice in retail and marketing to use these kind of insights and therefore I though posting this article in our blog may be useful.
How can Nokia Crowd Analytics help?
Nokia Crowd Analytics is a valuable datasource that can be used in several phases of the advertising campaign. Based on signals from mobile networks, it anonymously measures the location and movement of crowds through time without exposing any individual personal information. For example, a retail business owner can improve his decision making by identifying where his visitors come from, work, live, shop, dine, or go for entertainment. Combined with socioeconomic data related to the places where people spend their time, Nokia Crowd Analytics can provide valuable insights about existing customers. Moreover, those insights can also help marketers define their target audience by revealing gaps in the existing customer base. For example, a shopping mall owner may learn that a small number of mall visitors live in a wealthy neighborhood and therefore decide to define this neighborhood as a target of the next offline campaign. A hotel manager may observe that visitors within a specific income bracket originate from a certain remote city and decide to start an online campaign to address that particular group.
Nokia Crowd Analytics can also play an important role in measuring a campaign’s (both online and offline) impact, especially in terms of the number of visitors ie. to a retail outlet before and after the campaign. Likewise, this method can also be leveraged to better understand the performance and impact of a competitors’ campaign and plan your own moves accordingly.
Today, Nokia Crowd Analytics is intended to provide daily, weekly and monthly reports about the historical behavior of crowds over certain time periods.
To take advantage of Nokia’s unique offering of Crowd Analytics reports, explore these links:
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