Integrating B2B data to enhance your business strategy

Simply put, the more information you have in business, the better decisions you can make to drive the growth of your company.

Utilising external data through integrations offers a lot of advantages for the end user, such as understanding your competitors, improving your products or services, enhancing talent sourcing strategies, building data-driven products, and more.

The key benefits of integrating B2B data in your business strategy

When it comes to strategic planning, organisations that effectively utilise external data have a greater potential to outperform their competition. Benefits include:

Competitor Analysis

By leveraging data integration, businesses gain a deeper understanding of the market they operate in and their competition, giving them a competitive edge. And by analysing the competitive landscape through data integration, companies stay ahead of the pack in the market.

Implementing diverse data strategies within the organisation adds significant value by providing a comprehensive view of overall performance, as well as identifying market opportunities and potential threats.

Thorough company analysis

Big data is big business. Embracing big data empowers business leaders to tap into time series and historical data, enabling them to gain valuable insights into past successes and failures. By leveraging this wealth of information, they can make more informed, data-driven decisions moving forward.

Harnessing the insights derived from data, organisations can optimise the performance of various departments within their company. Additionally, they can benchmark specific aspects of their performance against competitors, gaining a deeper understanding of where they stand in the market and identifying areas for improvement. This data-driven approach enables businesses to stay ahead of the curve and drive continuous growth.

Lead generation

External data provides valuable information about the target audience, including demographics, behaviour patterns, and preferences. By analysing this data, businesses can refine their buyer personas and create highly targeted marketing campaigns. This enables them to reach the right prospects with personalised messages, increasing the likelihood of generating quality leads.

Integrating business data can also be used to build predictive models that help identify patterns and trends in lead generation. By analysing historical data and external market indicators, businesses can predict future lead generation outcomes more accurately. This enables proactive decision-making, allowing businesses to allocate resources effectively, optimise lead generation strategies, and adapt to market changes swiftly.

Strategic planning support

A truly effective company strategy goes beyond solely analysing internal data and delves into the realm of external data through integrations. By seeking out and leveraging the integrated data, organisations gain valuable insights that contribute to building more accurate predictive models. This broader perspective allows businesses to make informed decisions, anticipate market trends, and stay ahead of the competition, ultimately driving success and growth.

How different corporate departments integrate their business data

Sales and Business Intelligence

Professionals can leverage business data to generate new sales opportunities, find new opportunities for growth and also enhance their pitch intelligence with contextual and historical data.

Filter companies by location, founding date, industry, employee size and more to help find the best opportunities.

Talent Sourcing

Recruiters and HR professionals can use people data to enhance their talent sourcing strategies. They do this by generating lists of potential candidates, as well as monitoring the industry for people movements. By using this data, recruiters and HR professionals can find the best candidates from any company across Australia.

Filter people data by location, industry, experience and recent job movements to find the best employees that suit your company’s needs.

Data Driven Product Development

Business professionals can use company and product review data to analyse the market, and develop products best suited to their target market. They can also use employee reviews to develop their number one resource – people!

By directly accessing information from consumers and users, data driven product development will ensure your go to market strategies will suit the end user of your product or service.

Filter companies by tech stacks, reviews and key business details (ABN, company size etc.) to develop new products based on consumer needs.

Growth Marketing

Growth Marketing professionals can use social media, website and advertising data to drive their marketing campaigns to a new level. By leveraging the data collected from their competitors and clients, they focus their target marketing efforts to attract new customers and prospects.

Filter companies by paid and organic keywords, reviews and tech stacks to target your growth marketing campaigns in line with your market.

The difference between internal and external data integration

Internal data is collected by organisations in their operations and transactions. External data is collected by third parties, data marketplaces and more. See the full breakdown of the differences below:

Internal Data
External Data
Internal databases
Public or private sources
Collected By
Internal data teams
Data scientists
Systems and processes
Third-party organisations
Data marketplaces
Data brokerage agencies
and more...
Data Collection Methods
Primary and secondary data collection methods
Secondary data collection method
Data Quality


Organisations can significantly enhance the effectiveness of long-term business decisions by maximising the utilisation of publicly available external data. To unlock the most valuable insights, businesses should integrate their internal data with the existing external data sources. Furthermore, it is crucial for organisations to establish a robust data strategy that enables them to effectively evaluate and handle diverse data sets.

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