QuoteWay offers extensive Email Address Data, perfect for businesses seeking high-quality consumer information. This Email Address Data includes approximately 1.3M records, specifically gathered for life insurance purposes and currently resting for about 3 months without contact. Our B2C Contact Data boasts 96% valid postal codes (address data), 98% valid emails, and 70% valid phone numbers.

Our Canadian B2C Email Address Data can be used the following ways: - Marketing Campaigns: Utilize our Email Data to launch targeted marketing campaigns with accurate contact information. - Sales Lead Generation: Enhance your sales lead generation efforts by accessing verified B2C Contact Data. - Customer Profiling: Create detailed customer profiles on our Audience Data using our comprehensive B2C Contact Data. - Direct Mail Campaigns: Execute effective direct marketing campaigns with our B2C Contact Data's 96% valid postal codes and address data. - Email Marketing: Boost your email marketing success rates with 98% valid email data from our B2C Contact Data, allowing for direct marketing. - Telemarketing: Improve telemarketing outcomes with our audience data using 70% valid phone numbers in our B2C Contact Data. - Market Research: Conduct thorough market research with reliable B2C Contact Data for accurate consumer insights.

Key Benefits of our Email Address Data: - High Accuracy: Our B2C Contact Data is verified with 96% valid postal codes, 98% valid email data, and 70% valid phone numbers. - Large Dataset: Access a substantial dataset of approximately 1.3M records. - Fresh Data: The B2C Contact Data has been resting for about 3 months, ensuring it is not overused. - Versatile Use: Suitable for various applications such as marketing, sales, and research. - Compliance Ready: Our audience data is ready to use under QuoteWay Canada Inc., ensuring compliance and ease of use. - Life Insurance Focused: The data was initially collected for life insurance purposes, providing a unique consumer segment. - Reliable Source:QuoteWay's commitment to quality ensures that our B2C Contact Data is reliable and effective.

By leveraging QuoteWay's Email Address Data, businesses can achieve greater accuracy and success in their consumer outreach efforts. The comprehensive and verified nature of our B2C Contact Data makes it an invaluable resource for any organization looking to enhance its contact database.

According to a survey conducted between July 2020 to June 2021, approximately 35 percent of Canadians always choose not to be included in mailing lists. By comparison, roughly 31 percent is not of the same opinion and appears to be more inclined to receiving newsletters and other content via e-mail.

The Canadian Wind Turbine Database contains the geographic location and key technology details for wind turbines installed in Canada. This dataset was jointly compiled by researchers at CanmetENERGY-Ottawa and by the Centre for Applied Business Research in Energy and the Environment at the University of Alberta, under contract from Natural Resources Canada. Additional contributions were made by the Department of Civil & Mineral Engineering at the University of Toronto. Note that total project capacity was sourced from publicly available information, and may not match the sum of individual turbine rated capacity due to de-rating and other factors. The turbine numbering scheme adopted for this database is not intended to match the developer’s asset numbering. This database will be updated in the future. If you are aware of any errors, and would like to provide additional information, or for general inquiries, please use the contact email address listed on this page.

Air Quality Research Division, Environment and Climate Change Canada,

4905 Dufferin Street, Toronto, Ontario, M3H 5T4, Canada

Email: Junhua.zhang@canada.ca

The first version of a U.S.-EPA-BELD4-equivalent landuse database for Canada was compiled in 2018 by Environment and Climate Change Canada (ECCC) based on: (1) the first version of Canada-wide tree species composition maps based on the 2001 Canadian National Forest Inventory (NFI; Beaudoin et al., 2014); (2) the 2016 Canadian Annual Crop Inventory (ACI); and (3) the Land Cover Classification System surface hydrology (LCCS3) data set contained in the Collection 6 MODIS Land Cover product MCD12Q1 (Zhang and Moran, 2018). Recently, an improved mapping approach for estimating forest attributes from MODIS imagery was applied to reprocess the 2001 NFI-based species composition maps and to create a new set of species composition maps for 2011 using 2011 MODIS imagery (Beaudoin et al., 2017a,b). The new mapping approach resulted in an improved set of 2001 species composition maps as indicated by increased correlation coefficients and decreased mean deviations (MD) and root-mean-square deviations (RMSD) between 35,305 MODIS reference pixels for 2001 and the 2001 NFI photo-plot product (Beaudoin et al., 2017b). In addition, for the new 2011 species composition maps, expected reductions in forest coverage were seen for areas of Canada that had experienced rapid development between 2001 and 2011, such as the Athabasca Oil Sands (AOS) area in northeastern Alberta and areas near major urban centres such as Toronto and Vancouver. Given the improved mapping approach and the greater recentness of the 2011 tree species composition maps, the Canadian BELD4 landuse database was updated using these new 2011 maps and the same methodology described in Zhang and Moran (2018). Note that no change was made to the ACI and MODIS Land Cover product data sets that were used to develop this new database version.

Because the number of tree species considered in the 2001 NFI-based forest composition maps was reduced from 109 in the first version to 75 in the second version due to the least abundant tree species being lumped with other related species (Beaudoin et al., 2017b), gridded fractional-coverage fields for the U.S.-EPA-BELD4-equivalent landuse categories compiled for Canada have also been reduced, from 92 in the first version of the Canadian BELD4 database to 80 in this second version. The mapping from the 75 NFI tree species to the U.S. Environmental Protection Agency (EPA) BELD4 landuse categories is shown in the attached spreadsheet “ACI_NFI_BELD4_species_match_V2.xlsx”, along with the unchanged mapping of 62 ACI species and other landuse categories. The mapping used to link the LCCS3 categories to the BELD4 categories also remains unchanged and is described in the attached Excel file “MODIS_LCCS3_BELD4_mapping.xlsx”.

The updated version 2 of the Canadian BELD4 landuse database is provided here in GeoTIFF format at 1-km resolution for a Lambert conformal conic projection (+proj=lcc +lat_1=49 +lat_2=77 +lat_0=0 +lon_0=-95 +x_0=0 +y_0=0 +ellps=GRS80 +units=m +no_defs) in the compressed file “CAN-BELD4_tif_V2.7z”. Note that to use this dataset in conjunction with the U.S. EPA BELD4 database (https://www.epa.gov/air-emissions-modeling/biogenic-emission-sources), all MODIS landuse categories in the original EPA BELD4 database must be removed for Canada to avoid double-counting. Plots of the 80 matched Canadian and U.S. BELD4 vegetation species and other landuse categories in the new Canadian BELD4 database are shown in the attached file “CAN_US_Matched_BELD4_Species_Plots_V2.pdf”. Lastly, an overview and description of the updated Canadian BELD4 landuse database was presented at a recent conference (Zhang et al., 2019, https://www.epa.gov/sites/production/files/2019-08/documents/800am_zhang_2_0.pdf); this presentation is also provided in this package as file “2019EI_Updated_BELD4_Impact_on_VOC_emissions.pptx”.

REFERENCES

Beaudoin, A., Bernier, P.Y., Guindon, L., Villemaire, P., Guo, X.J., Stinson, G., Bergeron, T., Magnussen, S., and Hall, R.J.: Mapping attributes of Canada’s forests at moderate resolution through kNN and MODIS imagery. Canadian Journal of Forest Research, 44, 521–532, https://doi.org/10.1139/cjfr-2013-0401, 2014.

Beaudoin A., Bernier P.Y., Villemaire P., Guindon L., Guo X.-J., Species composition, forest properties and land cover types across Canada’s forests at 250m resolution for 2001 and 2011. Natural Resources Canada, Canadian Forest Service, Laurentian Forestry Centre, Quebec, Canada, https://doi.org/10.23687/ec9e2659-1c29-4ddb-87a2-6aced147a990, 2017a.

Beaudoin, A., Bernier, P.Y., Villemaire, P., Guindon, L., Guo, X.-J., Tracking forest attributes across Canada between 2001 and 2011 using a kNN mapping approach applied to MODIS imagery, Canadian Journal of Forest Research, 48: 85–93, https://doi.org/10.1139/cjfr-2017-0184, 2017b.

Zhang, J. and Moran, M. D., U.S.-EPA-BELD4-Equivalent Landuse Database for Canada [Data set]. Zenodo. http://doi.org/10.5281/zenodo.2231047, 2018.

Zhang, J., Moran, M.D., and He, Z.: Updates to Version 4 of the Biogenic Emissions Landuse Database (BELD4) for Canada and Impacts on Biogenic VOC Emissions, 2019 International Emissions Inventory Conference, July 29th – Aug. 2nd, Dallas, Texas, USA, https://www.epa.gov/sites/production/files/2019-08/documents/800am_zhang_2_0.pdf, 2019.

AcknowledgementS

We are very grateful for the dedicated assistance of Dr. Zhuanshi He of SOLANA Networks Inc. in preparing this updated version of the database.

RELATED DATA SETS AND MATERIALS

“CAN-BELD4_tif_V2.7z” – Version 2 of the extended BELD4 GeoTIFF file for Canada

“ACI_NFI_BELD4_species_match_V2.xlsx” – Version 2 of the NFI/ACI-BELD4 landuse-category crosswalk file

“MODIS_LCCS3_BELD4_mapping.xlsx” – MODIS-BELD4 landuse-category crosswalk file (same as in Version 1)

“CAN_US_Matched_BELD4_Species_Plots_V2.pdf” – Plots of 80 updated BELD4 landuse category fields over Canada.

“2019EI_Updated_BELD4_Impact_on_VOC_emissions.pptx” – 2019 conference presentation on this new version of the Canadian BELD4 landuse database

Here, we’re looking at other elements that may play a role in how you run your email marketing campaigns and the average metrics you could expect.

Our address datasets contain all geospatial address data of Canada. You can use this data to send direct mail campaigns to households within a certain radius of your store, or to limit your online campaigns to viewers within a specific catchment area.

Address-Level Targeting in Canada

Spotzi Targeting users can also combine our address data with consumer demographics and behavior data - such as insights into purchasing habits or disposable income - to ensure that every campaign targets their best-fit customers.

• Spotzi Profiling uses the address geographical dataset to create detailed profiles of potential customers. By combining location data with demographic and behavioral information, it can provide insights into the preferences and needs of different customer segments. This can help businesses understand their audience better and create more effective marketing strategies.

• To generate targeted mailing lists, employ our profiling tools to begin delineating your target audience according to demographics, interests, and behaviors. Employ strategies for direct mail customer segmentation to categorize your audience into specific groups. After creating these groups, you can export a list of addresses for focused and effective direct mail campaigns.

• Certainly, you can create address lists by aggregating data based on various parameters such as Canadian 3-digit postal code (FSA) areas. For example, you can generate an address list by postal code, allowing you to target specific geographic regions efficiently. This segmentation strategy aids in tailoring your communication to the unique characteristics of different areas or localities.

• Yes, you can export this Canadian address list to Excel. Most mailing list databases and management systems offer the option to export data in various formats, including Excel. This facilitates easy integration with other tools and allows for seamless data analysis and manipulation.

• Absolutely. This dataset is well-suited for address validation, offering a comprehensive solution through various means. Utilizing an address validation checker, you can ensure the accuracy and completeness of each address. The address data validation process is further enhanced with our robust API, allowing seamless integration for efficient validation.

  Whether you're validating addresses locally or internationally, our international address validation capabilities cover addresses worldwide. This ensures that your data is reliable, adheres to postal standards, and is ready for successful implementation in diverse global contexts.

Government Electronic Directory Services (GEDS) provides public access to Government of Canada employee contact information as provided by participating departments. Encoded with the Latin Alphabet 1 (ISO 8859-1) character set. This is the dataset that contains all of the raw data within the Government of Canada Employee Contact Information system, not the searchable lookup. To search for contact information, please go to Government Electronic Directory Services (GEDS). (​​http://geds.gc.ca)

Success.ai delivers comprehensive access to Small Business Contact Data, tailored to connect you with North American entrepreneurs and small business leaders. Our extensive database includes verified profiles of over 170 million professionals, ensuring direct access to decision-makers in various industries. With AI-validated accuracy, continuously updated datasets, and a focus on compliance, Success.ai empowers businesses to enhance their marketing, sales, and recruitment efforts while staying ahead in a competitive market.

Key Features of Success.ai's Small Business Contact Data:

Extensive Coverage: Access profiles for small business owners and entrepreneurs across the United States, Canada, and Mexico. Our database spans multiple industries, from retail to technology, providing diverse business insights.

Verified Contact Details: Each profile includes work emails, phone numbers, and firmographic data, enabling precise and effective outreach.

Industry-Specific Data: Target key sectors such as e-commerce, professional services, healthcare, manufacturing, and more, with tailored datasets designed to meet your specific business needs.

Real-Time Updates: Continuously updated to maintain a 99% accuracy rate, our data ensures that your campaigns are always backed by the most current information.

Ethical and Compliant: Fully compliant with GDPR and other global data protection regulations, ensuring ethical use of all contact data.

Why Choose Success.ai for Small Business Contact Data?

Best Price Guarantee: Enjoy the most competitive pricing in the market, delivering exceptional value for comprehensive and verified contact data.

AI-Validated Accuracy: Our advanced AI systems meticulously validate every data point to deliver unmatched reliability and precision.

Customizable Data Solutions: From hyper-targeted regional datasets to comprehensive industry-wide insights, we tailor our offerings to meet your exact requirements.

Scalable Access: Whether you're a startup or an enterprise, our solutions are designed to scale with your business needs.

Comprehensive Use Cases for Small Business Contact Data:

1. Targeted Marketing Campaigns:

Refine your marketing strategy by leveraging verified contact details for small business owners. Execute highly personalized email, phone, and multi-channel campaigns with precision.

1. Sales Prospecting:

Identify and connect with decision-makers in key industries. Use detailed profiles to enhance your sales outreach, close deals faster, and build long-term client relationships.

1. Recruitment and Talent Acquisition:

Discover small business leaders and key players in specific industries to strengthen your recruitment pipeline. Access up-to-date profiles for sourcing top talent.

1. Market Research:

Gain insights into small business trends, operational challenges, and industry benchmarks. Leverage this data for competitive analysis and market positioning.

1. Local Business Engagement:

Foster partnerships with small businesses by identifying community leaders and entrepreneurial influencers in your target regions.

APIs to Enhance Your Campaigns:

Enrichment API: Integrate real-time updates into your CRM and marketing systems to maintain accurate and actionable contact data. Perfect for businesses looking to improve lead quality.

Lead Generation API: Maximize your lead generation efforts with access to verified contact details, including emails and phone numbers. Tailored for precise targeting of small business decision-makers.

Tailored Solutions for Diverse Needs:

Marketing Agencies: Create targeted campaigns with verified data for small business owners across diverse sectors.

Sales Teams: Drive revenue growth with detailed profiles and direct access to decision-makers.

Recruiters: Build a talent pipeline with current and verified data on small business leaders and professionals.

Consultants: Provide data-driven recommendations to clients by leveraging detailed small business insights.

What Sets Success.ai Apart?

170M+ Profiles: Access a vast and detailed database of small business owners and entrepreneurs.

Global Standards Compliance: Rest assured knowing all data is ethically sourced and compliant with global privacy regulations.

Flexible Integration: Seamlessly integrate data into your existing workflows with customizable delivery options.

Dedicated Support: Our team of experts is always available to ensure you maximize the value of our solutions.

Empower Your Outreach with Success.ai:

Success.ai’s Small Business Contact Data is your gateway to building meaningful connections with North American entrepreneurs. Whether you're driving targeted marketing campaigns, enhancing sales prospecting, or conducting in-depth market research, our verified datasets provide the tools you need to succeed.

Get started with Success.ai today and unlock the potential of verified Small Business ...

Contact information for publicly funded schools in Ontario. Includes: * region * board number * board name * board type * board language * school name * school number * school level * school language * school type * school special conditions code * suite * PO box * street * city * province * postal code * phone number * fax * grade range * date open * school email * school website * board website Source: Board School Identification Database (BSID) / Ontario School Information System (OnSIS) as updated/maintained by boards, April 2025. Time Period : 2025-04-04 to 2025-04-04 Note: school and board contact information are updated/maintained by boards. Data includes: public and Catholic schools; publicly funded hospital and provincial schools; summer and night schools; Education and Community Partnership Programs (ECPP). Data excludes private schools. Also note: * Grade Range 9-12 may include pre-grade 9 * "Combined schools" offer both elementary and secondary education * school special conditions code "Not applicable" indicates that there are no special conditions for the school