Spending patterns- a BIG window into your consumers’ lifestyles
Technology, while on one hand has spoilt the consumer for choice, on the other hand, has left marketers grappling with clutter- multiple devices, channels, and platforms- and a distracted consumer. To break through this clutter, marketers need to often make sense of the deluge of data created by consumers and find ways to seem relatable and useful.
Brands and marketers across categories are constantly trying to get a 360-degree view of the target audience in order to engage better, broaden the user base, and maximize revenue.
With a 360 degree view of audiences, brands can:
In order to derive actionable intelligence about consumers, brands need to look at various aspects of their consumer lifecycle.
So what are your consumers doing?
Marketers need to understand various aspects of a user journey to determine the most suited user segments, subsegments, and personas they want to target before planning their marketing spend. This involves understanding online patterns such as favored products or most searched categories and buying frequency. Brands also need to merge the online behavior with real-world indicators such as home and work locations, frequently visited stores, places of interest for leisure activities, and spending pattern insights that tell where are consumers spending their money the most.
Here is an example of what a complete picture of a consumer looks like.
Near provides actionable intelligence from consumers’ real-world behavior patterns along with their spending patterns. Intelligence on offline interests, brand affinities, home locations, and dwell time when added to insights about where and when consumers are spending their money, can offer a wide and deep view into consumer behavior and lifestyles.
Through its partnership with Mastercard, Near can now provide a detailed view into the real-world behavior of top spenders across a wide range of categories such as Travel, Auto, Entertainment, Technology, Fashion, etc. For example, marketers can easily get intelligence about where do the top 25% spenders in the children’s apparel category live, which brand stores do they visit frequently- for how long, and what is their age and gender?
The Near platform combines data from spending behavior and real-world signals at the most granular level to derive consumer segments. These segments are then made available in Allspark, Near’s audience curation, and activation solution.
All this can be done with Near in a privacy-led environment and all the consumer data that is used is anonymized.
High-value and high-scale cohorts
With Near, brands and marketers can execute pinpointed targeting to consumer segments who specifically fulfill predetermined criteria. For example, a person who is essentially found reading travel-related content, seen frequently at airports, and spends a considerable amount of money at airport-based stores is a ‘Traveler’.
Near makes it easy for brands and agencies to engage better with the total number of audiences who were seen at a certain location spending on a certain category. Marketers who need to reach out to a wide audience base can easily use a scalable audience that is relevant to the campaign objective.
Globally, Near offers data intelligence about the visitation and other real-world patterns for about 1.6 billion users and spending data for 52 billion transactions per year.
In Australia alone, Near covers a massive scale of detailed spending data giving enormous and accurate intel to brands and marketers.
Spending pattern gives insights into affluence level, spending power, and to a great extent can tell the likelihood of future buying from a brand or category. These insights, when added to other real-world signals, can be used across categories to segment, target, and measure marketing campaigns more efficiently.
As a marketer, whether your goal is to drive more consumers in-store, convert more online visits into real buys, or simply widen your user base, knowing your audiences thoroughly can go a long way. Intelligence on spending patterns and real-world consumer behavior are two paramount dimensions to help you know them and personalize at scale.
Mastercard is a multinational financial services corporation. The global giant has access to over 2.3 billion cards and 52 billion transactions per year globally. The Near platform processes and offers intelligence on data from 1.6 billion global users and 70 million places. With its partnership with Mastercard, the scope of Near’s data has further increased immensely.