Mining the Undiscovered Market Using Location and Data to Target Growth
•Download as PPTX, PDF•
0 likes•71 views
Global telecom providers generate the most revenue and strengthen customer loyalty when they have a deep understanding of their best coverage areas. This requires knowing who their customers are, where they need coverage, and how they interact with telecom services. Global geocoding, location analytics, and comprehensive data can help reveal these vital insights. Layering multiple datasets related to demographic and address information provides an in-depth view of telecom markets around the world. Locating existing customers or prospects and enriching their profiles with attribution related to age, education level, ethnicity, income, and expenditures gives telecom providers the detail they need to develop strategic products, services, and campaigns. Join this webinar to understand how to leverage global location intelligence and demographic data to boost revenue and customer satisfaction. Register now and learn more about: - Analyzing coverage areas with address data and geocoding - Identifying lookalike markets with globally consistent demographic data - Layering multiple datasets to develop an accurate view of customers and coverage areas
Recommended
Recommended
More Related Content
What's hot
What's hot (12)
Similar to Mining the Undiscovered Market Using Location and Data to Target Growth
Similar to Mining the Undiscovered Market Using Location and Data to Target Growth (20)
More from Precisely
More from Precisely (20)
Recently uploaded
Recently uploaded (20)
Mining the Undiscovered Market Using Location and Data to Target Growth
- 1. Mining the Undiscovered Market Using Location and Data to Target Growth Tim McKenzie Briana Brown
- 2. Leveraging Location Intelligence Enriched with Demographic and Consumer Data • How do we increase ROI by marketing to the right consumers with the right message at the right time and in the right place? • How can we identify and target new customers in our strongest coverage areas? • How can we geo-enrich new address information from multiple data sources so that commercial and consumer information can be added to network analytics? • How has COVID 19 shifted consumer daily living patterns for where people work, play, & live and how can we better serve them?
- 3. Introducing Precisely • The merger of Pitney Bowes Software and Data and Syncsort • Precisely offers powerful data integration and optimization software alongside best-in- class location intelligence, data enrichment, customer information management and engagement solutions. • 12,000 customers • 90 of the fortune 100 • Customers in more that 100 countries • 2,000+ employees Portfolio: • Integrate • Verify • Locate • Enrich • Engage Headquartered in Pearl River, NY with offices across North America, EMEA, Asia Pacific to support our global customers and partners.
- 5. The Forrester Wave™: Location Intelligence Platforms, Q2 2020 5 Precisely • Esri and Precisely (formerly known as Syncsort) were the only LEADERS in Location Intelligence Platforms • Oracle and Microsoft are Strong Performers • Hexagon, MapLarge, CARTO, Salesforce, Google are Contenders The Forrester Wave™ is copyrighted by Forrester Research, Inc. Forrester and Forrester Wave™ are trademarks of Forrester Research, Inc. The Forrester Wave™ is a graphical representation of Forrester’s call on a market and is plotted using a detailed spreadsheet with exposed scores, weightings, and comments. Forrester does not endorse any vendor, product, or service depicted in the Forrester Wave™. Information is based on best available resources. Opinions reflect judgment at the time and are subject to change.
- 6. Comprehensive data integrity capabilities Real-time Replication App & Machine Data Integration High Availability Mainframe Data Integration Integrate Data Profiling Data Cleansing Entity Resolution Address Validation Context Graph Verify Addressing Spatial Analysis Geocoding Routing Visualization Locate DATA Over 9,000 Attributes Consumer Insights Geographic Business Point of Interest Boundaries Industry-Specific Data Demographics Enrich Customer Experience Customer Communication Digital Self Service Engage
- 7. Locate
- 8. Master Location Data with PreciselyID Accurate & Validated Location Data Merge De-dup Standardize Build linkable data Pre-score the country Find “hidden” addresses Simplify Synchronization Build Personas Assign PreciselyID
- 9. PreciselyID – Enabling Enrichment Sales and marketing optimization Build rich target personas Robust consumer insights 5G buildout Subscriber analytics PreciselyID
- 10. Location Intelligence + Demographic Data Demographics and Geodemographic Segmentation • Aggregated and anonymized data • Neighborhoods are categorized in terms of the characteristics of the population which they contain • No Personal Identifiable Information (PII) Consumer Data • Individual and household level data • Resolve identities based on digital identifiers (email, phone, name and address, etc.) • Contains Personal Identifiable Information (PII)
- 11. Types of Demographics DEMOGRAPHICS Typically limited to the base year of collection or current year and are most useful to clients who have an analytics team and wish to perform their own analyses ESTIMATES & PROJECTIONS Provide data beyond the base collection year including current year estimates and three, five or 10-year projections GEODEMOGRAPHICS Preconfigured segmentation of the population into lifestyle groups where the analytics have already been performed • Count or % of Resident population aged 18-24 • Count of % of Single Person Households • Current Year Estimate Total Population • 2023 Estimate Population Aged 18-24 • “Professional Urban Families” • “Metro Success” • “Settled and Single”
- 12. CAMEO USA Category CAMEO USA Type 1 1A High Society Families 1B Upper Crust Households 1C Asset Rich Families 1D Elite Suburbs 1E Moguls And Mansions 2 2A Skyscraping Nouveau Riche 2B Subtopia 2C Cosmopolitan Suburbia 2D Old Money 3 3A High Flying Families 3B Urban Movers And Shakers 3C Middle Class Managers 3D Professional Urban Families 3E Affluent Established Suburbia 3F Escape To The Country 4 4A Big City Startups 4B Middle Age, Middle Class 4C Urban Success 4D Urbane Melting Pot 4E Settled In The Suburbs 4F Rural Empty Nesters 5 5A Big City Hipsters 5B School Run Families 5C Small Town Suburbia 5D Settled In The City 5E Close To Retirement, Out Of Town 5F Mature Suburbs 5G Comfortable In Retirement 6 6A Studying In The City CAMEO USA Category CAMEO USA Type 6B Suburban Sharers 6C Big Family Values 6D Diverse Urban Mix 6E Settled And Single 6F Established Traditional Neighbourhoods 6G Retirement Communities 7 7A Flown The Nest 7B Struggling Scholars 7C Fledgling Urban Families 7D Coastal Chic 7E Downtown Tenants 7F Maturing In Middle America 7G Retiring Renters 8 8A New Kids On The Block 8B Urban Endeavours 8C Bohemian Broods 8D Blue Collar Bourgeoisie 8E Provincial Fusion 8F Golden Oldies 9 9A Urban Start-Ups 9B Cramped City Families 9C Big City Small Wallet 9D Small Town Family Struggle 9E Low Income Melting Pot 10 10A Stretched Family Start-Ups 10B Struggling Young Families 10C Hard Up Households 10D Big Town Austerity 10E Homeowners In Hardship XX Unclassified / No Population Data Precisely Geodemographics
- 14. Create a Profile for a Location • Digital billboard location • Want to know potential audience socio-economic or lifestyle profile • Overlay a geodemographic system • Estimate a catchment radius • Example profile: • Aspiring Consumers • Prosperous Families • Exclusive Society • BUT this is the resident (nighttime) population only • Populations are dynamic and mobile Presentation name
- 15. Create a Dynamic Profile for a Location • Again, we can use a geodemographic system to help us understand audience profiles • To uncover population mobility can use mobile trace data (weekday mornings, 2 weeks in Feb) • How do inflows of population change the potential audience? • Population flows into the location are drawn from all over city and include many different geodemographic groups • These inflows of population change the location audience Inflows of Population: Mobile TraceOrigins of Flows to One Destination
- 16. Create a Dynamic Profile for a Location Inflows of Population: Mobile TraceOrigins of Flows to One Destination Chart 1: Resident profile Chart 2: Resident profile plus inflow
- 17. Logo Identity Household Lifestyle Income Purchases Social Handles Risk Drive Times Points of Interest Property Attributes Postal Address PreciselyID Connect individuals to a location. Understand your customers with: • 184 million U.S, addresses • Over 260 million consumer profiles • Key information about an address • A true 360⁰ customer view • Detailed consumer information for trade area analysis and retail site selection With Consumer Data Insights you can: • Create target audiences based on geography • Improve risk assessment • Better understand a location by knowing who lives there Consumer Data Insights
- 18. Connect Offline and Online Data for True Insights We bring together and complete fragmented customer data and market data to enable 360° identity resolution and consumer data insights at scale INBOUND CHANNEL WEBSITE APPS RETAIL STORE SOCIAL CUSTOMER CARE LOYALTY
- 19. Custom Custom-create your own data pack that aligns to your exact insight needs. Social Affinities Attributed likes, interests and activities of individuals based on information they have shared via social media websites. Core Consumer A wide range of data including demographic, employment, education, and social identities. Households Learn more about your customer by understanding the home they live in and who they share their lives with. Auto Ownership Detailed vehicle ownership records compiled from a variety of sources. Finances Gain insight into your customers’ financial status including household discretionary income, net worth, bankruptcy, and debt. Email Hash Email Hash will return hashed versions of known email addresses associated with a matched profile. Purchases & Shopping Discover what else your customers are spending their money on beyond your products and services. Lifestyles An assortment of data to paint a detailed picture of your customers - includes hobbies, travel propensities, and product ownership. Consumer Data Insights
- 20. Media Amplification Extend Media Reach To Improve ROI Gain Incremental Media Touchpoints Enrich profiles with an input or inputs, such as: name/address, phone number, or email, and append Hashed Emails and Mobile Ad IDs to: ● Extend Media Channels & ROI ● Increase Media Performance Through Coverage ● Gain Long-Lasting Identifiers Jessie Lee CoreID: PYU87B Input: Mobile Ad ID 0d20b201-8de3- 4025-8302-3f21aaad1b32 Jessie Lee 34 Main Street Austin TX, 78702 Jessie12@gmail.com512-553-4432 Mobile Advertising ID: 0d20b201-8de3- 4025-8302-3f21aaad1b32 Output: Multiple Mobile Ad IDs and Hashed Emails Hashed Email: 8576458dfcb259408aa5b2b 0ec640e810c9991bbf45df7a6f8bc80c9
- 21. Consumer Data and Location for improved Targeting Enrich by location • Learn more about users who are not the primary account holder • create targeted audiences based on a geography Enrich existing client and prospect lists • Resolve identities • Target one person more effectively • Create personalized messaging based on enriched profiles • Target NEW lookalike customers • Append digital identifiers for omni channel advertising campaigns • Hashed Email • MAIDs (Mobile Advertising IDs)
- 22. Mining the Undiscovered Market to Target Growth Summary Locate • Location Intelligence • Geocoding • Master Location Data Approach • Accurate Addresses • PreciselyID Enrich • Consumer Data Insights • Demographics • Estimates & Projections • Geodemographics
- 24. 24 Deployment Patterns for our Technology Traditional Server Deployment- All In One Platform running as a static server instance in a data center. Cloud Native Compute- Leverage Cloud Native Microservices managed by Kubernetes and other cloud technologies for dynamic and scalable processing. Software as a Service- Leverage the processing power of the cloud without the need to maintain and manage a deployment infrastructure.
Editor's Notes
- Fierce
- Tim Today I will be sharing some ideas and best practices about how telco clients can leverage location intelligence principles while enriching traditional spatial information with demographic and consumer data can allow CSP’s to drive efforts such as: Identifying potential new subscribers in an existing coverage area Understanding new services that your existing customers may find valuable Delivering hyper-targeted messaging or offers Knowing which products or services may resonate within in a specific geographic area Or even knowing that at morning rush hour a neighborhood street segment may have a very different lifestyle demographic that is just passing through on the way to work OR, NOW with COVID 19 many of the demographic modeling that marketers thought was predictable and may have become comfortable with--all of this has just been upended as so many social norms are in flux as mom, dad, the kids, and grandma are all in the house at 10 AM on Tuesday doing remote work and school. Our view is that to do this well it depends on having precision around location coupled with a rich set of data attributes that can be applied to any current subscriber or residential and business addresses. We’ll get into this more…
- CHRIS: But first a little about Precisely for those who are unfamiliar with the name…
- CHRIS: <opening story>
- Tim As I mentioned previously, Forrester identified an entirely different analyst to conduct the survey in 2018 and the same analyst conducted the 2020 survey recently. The prior survey analyst was perhaps too generous to the other vendors and so you see some slippage in rank by those vendors such as Oracle. It is interesting to note the appearance of new suppliers and the exit of some competitors in 2018. If you perceive from this chart the PB is slightly ahead of Esri on the vertical axis you would be correct … Alteryx and SAP are gone, and MapLarge has moved from being a Strong Performer to that of a mid-level Contender. Compared to 2016, all the players that remain, went a bit backward…so, for Syncsort/PB to remain in a leadership position is significant.
- Tim Today we’ll be focusing on our Locate & Enrich solution stacks. I’ll begin by introducing Locate and Briana will follow up with some concepts and details around enrichment.
- Tim Telco providers already have a wealth of existing subscriber location information obtained from devices and their networks. For instance, a provider may have the exact GPS coordinate of an existing subscriber at a given time, but are they able to tie that location coordinate information to types of businesses (eg. grocery , insurance agency, gas station) or even the business names of those businesses in the immediate vicinity? If they could, are there partnerships that could be leveraged? Could a marketing offer be sent via text, email, or embedded into a browser advertisement? This is where we may say, it all starts with location Our Locate solutions are comprised of software and datasets the ensure our clients have access and can resolve the most challenging location intelligence queries. Whether it’s using an address validation engine to make sure a given address is correct and located at the correct latitude/longitude (also known as a geocode), or doing the reverse of that and taking the geocode and associating the nearest address, business, or any number of points of interests like a park or school we our solutions can help ensure the location is correct. Having this foundational address accuracy is paramount for every use case, for we all know the feeling when our GPS says “You’ve Arrived!” and the ice cream shop is nowhere to be found. Of course, the locals know it’s just a little further up the road.
- Tim Building on the importance of location accuracy, is what we may call a Master Location Data approach. This is where we have purpose built into our Locate solutions the ability to not only be able to return accurate addresses or locations through our geocoding and address validation software and data, but that each addressable location would be associated to a unique and persistent identifier called PreciselyID. This provides a benefit of becoming a stable anchor point to tie, or join, additional insights to.
- Tim The PreciselyID provides with the ability for marketers and data scientist to easily enrich a record, or address, or to build a consumer profile. Once a record is associated with a PreciselyID, there is no need to reprocess that record through the process of geocoding through an address validation engine. And with over 9,000 possible attributes across our data portfolio there are unlimited use cases that can be supported PreciselyID can also be used with your existing house data or any 3rd party data. One example where marketers can use this is in creating customer profiles or ideal target personas which become intrinsically more valuable when a holistic 360 degree view with rich attribution is provided. PreciselyID can facilitate the joining of information such as household demographics, school district boundaries, home values and other attributes to your existing records. Briana will now walk us through how some of these concepts can be applied to specific marketing and customer acquisition use cases as he discusses the Enrich stack.
- Briana Now I’d like to talk about how we can use Location Intelligence -in combination with Demographics and Consumer Data to gain an intimate understanding of who is located in your best coverage areas, so that you can target them effectively In our Portfolio, Demographics and Consumer are two distinctly different types of data -that can be used together to build and support targeted marketing campaigns and create more personalized messaging for your existing customers Demographic and Geodemographic segmentation products consist of aggregated, anonymized data that is built to define neighborhoods, based on the people who live there Consumer Data enrichment solutions -provide data at an individual and household level -Our solution, Consumer Data Insights is based on the ability to resolve identities and return specific details about a person, and the household they live in So, with that quick overview I’d like to dive into how these solutions can be used in combination with location for improved targeting.
- Briana Precisely Demographics is a large and successful part of our Data portfolio. It consists of several data categories that help our clients understand people and the places where they live and work. Unlike our Consumer products, which I will talk about in a moment, all our Precisely Demographic products are aggregated to different geographies. This means that when I talk about demographics it refers to counts of people and their different attributes and characteristics in different neighbourhoods or locations. No personally identifiable information, or PII, is supplied in the products. So, an example would be the count or percentage of 18 to 24 year olds in neighbourhood X. Our Demographics products provide global coverage of elements such as population, age, gender, income and more, as they relate to local geographies. And our Demographics are standardised, meaning that for 140 countries covering billions of consumers we can provide the same data across socio-demographics, purchasing power, consumer spend plus a selection of additional attributes allowing true cross border analysis. Broadly speaking we divide the portfolio into three areas: Demographics, Estimates and Projections, and Geodemographics. These products can each be applied to specific use cases, but they all have the same overarching objective: and that is to enable clients to make better decisions with keener insight into who their customers are, what they need and where potential markets exist. Today I would like to focus the conversation and take a deeper look at Geodemographics
- Briana A geodemographic segmentation classifies and labels neighbourhoods based on the socio-economic and behavioural characteristics of their populations. It’s assumed that people who live in the same neighbourhood are likely to share similar characteristics. Neighbourhoods are categorized in terms of the characteristics of their resident population and then given a descriptive label to quickly better understand that population. A couple examples of category labels could be: “High Flying Families” or “Struggling Scholars” In essence, geodemographic classifications seek to simplify what is essentially a multi-dimensional problem – how to make sense of hundreds, even thousands of demographic variables, at a neighbourhood level and translate this into actionable insight for use in marketing campaigns, development planning and so forth. If we look at this slide, it shows some detail from our CAMEO USA geodemographic product. The product segments neighbourhoods into 58 discrete categories, which are in turn aligned to one of 10 groups. The map shows the distribution of the different groups in San Francisco and the list of groups and categories is shown in the table to the right. Examples of these categories are “Urban Success”, “Big City Hipsters” or “Downtown Tenants”. Using the PreciselyID, you can append these geodemographic codes and profile your customers, based on a simple look up table. Eliminating the need for complex spatial analysis. Or you can use this data, overlain with service coverage maps to identify areas for targeted growth, to help guide investments to extend network coverage or determine where to offer additional services, based on the composition of a neighborhood.
- Briana Sitting behind each of these labels is a host of data describing the segment – here we see some examples of what is typically included – this example here is from our UK product.
- Briana Next, I would like to look at some examples of how geodemographic data can help you understand the types of audiences who are likely to view ads at certain locations. Secondly, I’ll talk though how this customisation of the message can be refined by combining demographics or geodemographics with other datasets, such as mobile trace data. First, let’s consider how geodemographics can provide location intelligence. The map on this slide shows a fictitious location of a digital billboard in San Francisco, represented by the white dot. Without additional data to assist, the potential audience at this location is completely unknown. Understanding the audience that is likely to view the ads shown on this billboard is key to the success of any associated marketing campaign. In order to align or customize advertisements that are shown on the billboard we can use the pre-defined geodemographic segments that I talked about earlier to provide the first pieces of insight. The first step is to overlay the data. *CLICK* This now shows the socio-economic geography of the area. As you can see there’s a lot going on here, it’s complex and varied. However, we can start to create an audience profile based on the combination of the location of the billboard, plus the related geodemographic classification If we draw a catchment, or sphere of influence around that location then we can start to build a profile of the likely viewing population. *CLICK* In this case we can see that the catchment profile comprises “Aspiring Consumers”, “Prosperous Families” and “Exclusive Society”. From this, you can start to match the types of ads shown to these more affluent segments of the population. And because the segments are consistent across the country, this method can be rolled-out nationwide. *CLICK* Now, this approach can create great insight about a location, but there are some limitations to the data. Demographic data is generally created using large scale surveys such as censuses, or based at least in some part on estimates using survey data. These data sources collect information on residents of an area, or in other words the night-time population. So, while the local resident population may see the ad on the billboard, there is a very significant population who will be a visitor to that location – they could work in that location for example, or have gone out to lunch, or shopping. This inflow and outflow, of different population types can dramatically change the social geography of that location. And to add further complexity, these populations change throughout the day, and across different days of the week. In other words, geodemographic and demographic data do not currently reflect the dynamic nature of populations. So, how do we get around this and adjust for this use case? One option is to bring in another dataset that reflects these flows of population such as Mobile Trace data. This allows traces of population flows to be collected unanimously, the dots joined, and journeys defined. In addition all data is time stamped, so not only are we able to look at where populations go, we also know when they’re at a location. Knowing these points allows us to make a static dataset dynamic and time sensitive. So, what does this look like in reality?
- Briana Lets look at how we can CREATE A DYNAMIC PROFILE FOR A LOCATION Take our map of San Francisco again, with our geodemographic overlay. This shows the profile of the residential or night-time population. *CLICK* If we take mobile trace data and look at the inflows of population, then we can see significant movement occurring all over the city. The data that you’re looking at is inflows of population to neighbourhoods during weekday mornings for a couple of weeks in February (before movement was restricted due to COVID 19). Larger inflows are represented by larger circles. This is a pretty complicated picture – so let’s look at one neighbourhood only. *CLICK* The location we are going to concentrate on is indicated by the red circle to the east of the map. We can identify, from the mobile trace data, the origins of the flows into this neighbourhood – these are represented by the white dots scattered across the city. The size of the dots is proportional to the size of the flow of population from that origin into our destination location. So we can see that we get greater inflows of population from the adjacent neighbourhoods to the north where the dots are larger. So the question is, How do these inflows of population change the potential audience? Well, associated with each of the origin locations is a geodemographic segment – in other words, a socio-economic profile of that origin location. We can therefore assign this typology to the flow that travels to our destination. If we take all of the inflows of population to our destination, plus their geodemographic profile, then this obviously changes the audience at our location during weekday mornings.
- Briana If we chart this change, we see that the daytime population is much more diverse that the resident population – the top chart shows the residential geodemographic profile at our location. It’s predominantly made up of a couple of segments - Exclusive Society and Comfortable Communities. If we add in the profiled flows of population to our location then it changes the weekday morning profile to this – a different geodemographic profile where more segments are represented. By targeting advertisements to the residential audience profile, significant segments of the true audience are missing and targeting becomes less precise. This example is using Geodemographic segmentation. However, a similar approach could be applied using other data elements such as – age and income for example.
- Briana Our Consumer Data Insights solution is based on integrating consumer data with Location Intelligence It is an enrichment based solution supported by an Identity Graph with more than 260 million consumer identities and billions of contact points -Consumer Data Insights is different from our Demographics Data in that it is not aggregated To a block level or greater geography This data is at an individual and household level -Consumer Data Insights allows companies to: -Gain a better understand a location by knowing who lives around it -And a better understand an individual based on their surroundings To do this, we’ve leveraged our address database of over 190 Million US Addresses -and assigned a PreciselyID to each consumer record we have connected to a physical address in the Identity Graph -as Chis has described, this ID is a unique identifier for an addressable location that’s built into our products to enable data interpretability -making it easy to integrate consumer data with Location Intelligence For example, we can use the PreciselyID as an input, and return information about the individuals who live in a household -this is beneficial to our clients looking to identify a learn more about users who are not the primary account holder -We can also create targeted audiences based on a geography -for instance, you can Identify and target new customers who reside in your strongest areas of coverage By appending the PreciselyID to an individual we can also look at a consumer’s proximity to businesses and restaurants, retail areas, or places of recreation by connecting to our POI dataset -we can understand drive times to things like medical facilities and retail centers -We can pull in property attributes to understand details like square footage of their home, number of bedrooms, and even the mortgage date All these different datasets can be used to create more accurate audience profiles, and provide insight that can be used to capture people’s attention in advertising campaigns
- Briana But consumer enrichment does not need to start with location We have the ability to Resolve an Identity based on any fragment of information -We can take an Email, Phone, Name and Address or even a twitter handle, and resolve any combination of these contact points to a single individual -We then assign a CoreID, a unique identifier for an individual -This unique identifier can be used to connect disparate datasets, and de-duplicate client lists so that you can easily recognize individuals across different channels -Once we’ve resolved an identity, we can then append a wealth of information to learn more about the person behind the data Customer and prospect contact information -is captured a lot of different ways Whether its data collected via Point of sale purchases, website visits, social media or something like a customer loyalty program We can take this information And help our clients validate, fill in gaps and expand on the data they already have Enriched customer profiles provide data to better understand current customer segments, so that you can more accurately identify and target new lookalike customers
- Briana Consumer Enrichment products return various attributes to define individuals -Our solution, Consumer Data Insights consists of data packages, or attribute bundles that can be used independently or in combination to create detailed audience profiles The Core Consumer package is really the cornerstone, or foundation of this product line. - it returns basic information like Name, Age, Gender as well as attribution like marital status, employment, education, and even social profiles for an individual Once you have a basic understanding of an individual additional data packages can be used to create a more detailed audience profile The Social Affinities and Lifestyle data packages provide the likes and interests for an individual based on self reported information Purchases and Shopping attributes are based on actual consumer transactions that can be used to predict future behavior Household and Finance datasets provide a detailed understanding of the home environment and economic status of a consumer And we can even return details about the automobiles a person owns
- Briana In addition to profile enrichment, we return digital identifiers that enable marketing activation Targeted advertising is more successful used in conjunction with omni-channel campaigns -The success of an advertising campaign depends largely on the number of quality impressions created -Omni-channel advertising can obviously increase the number of impressions MAIDs and Hashed Emails enable targeted, personalized messaging through mobile applications and browsers -To elaborate incase any one isn’t familiar -Mobile Advertising IDs are a unique, anonymous identifier that are assigned to each mobile device for advertising purposes -Hashed emails are encoded representations of a plain text email address, that protects individual privacy but can still be used for digital On Boarding We can append up to: 3.2 MAIDs and/or Hashed Email per individual -greatly extending the marketing reach and number of quality impressions for an omni-channel campaign
- Briana So, how can you use Consumer Data and Location Data to improve targeted marketing? Enrich based on location using the PreciselyID and: return information about the individuals who live in a household Identify users when they are not the primary account holder create targeted audiences based on a geography Then you can enrich client and prospect lists to gain a better understanding of current customers -Resolving these identities, and assigning a unique identifier for each individual will help you do a couple things: 1st Understand the different channels a consumer uses to interact with your company 2nd you’ll be able to target one person more effectively -for example, you’ll probably have multiple target audiences and messages for a single campaign -a single individual could be your CRM database multiple times -identity resolution can help avoid conflicting messaging, and can help reduce costs for Omni- Channel campaigns Appended Consumer attributes then create greater insight into what your target customer looks like -providing fuel for improved audience segmentation and to create lookalike audiences to identify new high value customers -Audience segmentation and target customer profiles can then be used with Geodemographic data to determine when and where to focus marketing efforts to maximize the number of impressions with more personalized messaging, while controlling your marketing spend Lastly, append new Digital Identifiers to a customer record to enable successful omni-channel campaigns
- Tim
- Tim
- Tim