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Benefits of Data-Driven Referral Marketing Strategies in 2021 – ReadWrite

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Ekalavya Hansaj


As a business owner, regardless of your company’s size, you should be aware of what your customers want. Knowing precisely what your customers demand can help ensure the success of new products and services and ultimately increase your sales. Customer insights also allow you to adapt your business model to accommodate market trends and changes. But how do you find these data-driven referral marketing strategies and insights?

Benefits of Data-Driven Referral Marketing Strategies

Data-driven referral marketing is your secret weapon to achieving intimate knowledge of your customer’s preferences and buying habits. In fact, as most of our business practices are performed online, referral data should become the core informant of your marketing campaigns.

Wondering how this information affects your marketing campaigns? Learn more about data-driven marketing and how it can benefit your business in our guide.

What is Data-Driven Referral Marketing?

The Data-Driven strategy uses customer information to optimize how a brand communicates with its referred audience.

Referral marketers who rely on data-driven strategies use customer information to predict their audience’s:

  • Desires
  • Needs
  • Future habits

These three important insights will help your business develop effective referral marketing campaigns, with the ultimate goal being to achieve the most optimal return on investment (ROI). It makes sense that if you’re aware of what your customers want, need, and will need; you can plan your marketing and product lines accordingly.

Data-Driven Referral Marketing vs. Traditional Referral Marketing: What’s the Difference?

Essentially, data-driven marketing is the automation of traditional marketing processes. Let’s start with definitions of both:

Traditional referral marketing involves communicating and exchanging deals that hold value for clients. It’s a broad definition that encompasses any marketing activity used by companies pre-internet.

Traditional marketing relies on two factors to achieve an increased ROI.

  • Market studies. Before we used computers to gather data, we did it by hand. Market studies were conducted via interviews, consumer testing, and client feedback. They are lengthy and expensive to perform, so the past was not repeated or updated fast enough to keep up with changes in the market. They weren’t always the most accurate – but do still offer interesting insights.
  • Assumptions. A large part of traditional referral marketing relies on assumptions – guessing what customers want. For instance, a florist might assume that customers might also like the same flower in blue because their pink bouquet was a best-seller. This isn’t always the case and can mistakenly give a company’s ideal target audience.

Enter data-driven referral marketing, which almost eradicates the limitations of traditional marketing. Consumer data instantly shows referral marketers what people are buying, how much they’re willing to spend and gives valuable insights into trends and market gaps.

The use of data in referral marketing can be traced back to the invention of the first CRM (Customer Relationship Management) system.

First rolled out in the 1970s, early CRMs allowed companies to collect and store customer information. They began to track and use that data to create custom approaches to marketing.

With the use of CRMs in full swing in the 1980s and 1990s, companies began to mass-adopt methods like sales force automation and hotline numbers. These practices were essential to understanding and attracting different consumer demographics.

Data-driven referral marketing has slowly but surely allowed companies to create a personalized communication channel with their prospective customers.

CRMs have evolved in a big way since their main purpose remains consistent: to reach and engage consumers with customized messages that turn leads into sales.

The most crucial distinction between traditional marketing and data-driven referral marketing is the latter’s emphasis on targeted referral and advertising techniques.

Traditional marketing aims to appeal to the masses.

Data-driven marketing hones in on the customer, making the most of a referral marketer’s efforts.

The Benefits of Data-Driven Referral Marketing

Data-driven marketing is a complex process. There’s no formulaic way of implementing it that guarantees results. And, because of its versatile nature, it may be challenging to get on board with. However, when interpreted and used well, it works a charm.

It’s worth crunching data into your referral marketing strategies.

  • It creates personal relationships. This may seem counter-intuitive – using computer data to establish human relationships? But hear us out. It grants you a deeper understanding of your customer profile. It lets you create unique referral campaigns that speak directly to them. Consumers still respond better to personal and human-like connections despite our automated world, like targeted referral ads, than blind referral advertising.
  • It helps you define your target audience. Backed with facts, you definitively know who to target. Without them, you’re left guessing and wasting your time and resources trying to reach the wrong crowd.
  • It encourages product development. Armed with data about what your customers are buying, you can pinpoint what to improve and develop. Use this data to inform your product development processes and predict trends before they even emerge.
  • It improves customers’ experiences. Enhance your customers’ experience with your company by encouraging the completion of customer satisfaction surveys. This highlights critical areas that you can improve on.
  • It promotes the use of multiple channels. With insightful consumer referral data at your disposal, you can determine which channels are best to reach them. Through the use of automated referral marketing campaigns (email, social media, paid ads), you can deliver a consistent message that reaches each demographic through the ideal medium.

Related Information: “How to Use AI to create a Data-Driven Digital Marketing Strategy For Your Startup.”

Possible Challenges to Data-Driven Marketing

Though often effective, data-driven referral marketing is not a straightforward way of improving your marketing results. It’s important not to neglect some of the challenges that come with it, such as:

  • Ensuring you have clean and complete data. Improving data quality is always at the forefront of data marketers’ minds. Data can be incomplete, duplicated, or just incorrect. You must create a reliable process that keeps inconsistencies at bay. A good referral marketing strategy also ensures your information doesn’t become outdated.
  • Collecting data from several platforms. An effective referral marketing strategy involves integrating data from more than one platform. This can present issues because different referral sources have varying formats. You may end up with inconsistent and duplicated referral data and information. You must identify referral marketing variables that skew information and form discrepancies between your different referral data collection methods.
  • Tracking the right marketing key performance indicators (KPIs). When you first dive into data-driven referral marketing, it can be tempting to track every piece of referral data you can. This is a waste of your time and referral marketing resources. To find referral marketing KPIs that are worthwhile to track, you should identify your company’s big-picture goals. Determine what types of referral marketing data contribute to them. From there, you can reconsider the KPIs your company measures. Add new KPIs or get rid of irrelevant ones. Determining which KPIs to keep track of is a never-ending process. You should always be willing to revisit your referral marketing plan and make adjustments as needed.

When faced with these challenges, don’t be discouraged — you can overcome these with the right commitment and team by your side.

How to Implement a Data-Driven Marketing Strategy

Here’s how to plan and implement a data-driven referral marketing strategy. Keep in mind that this is just an outline. Don’t hesitate to alter these steps to fit your company’s and customers’ needs best.

1) Collect Referral Data

You will need the right referral customer information to use as a launching point.

Collect data every time a referred customer comes into contact with your brand. An easy way to collect referral data is to take advantage of every interaction your customer has with your company. For example, capturing email addresses through creating account profiles, or, if a referred customer requests to join your webinar, require them to complete a form that includes information like their location of work and job title.

Another way could be asking a referred buyer to fill out a post-purchase survey that asks for additional information you would otherwise miss out on, such as their age and gender. Small requests like these to collect data about your consumer demographics are essential. They will go a long way for your future referral marketing efforts and help you better perform the steps to come.

2) Build Unique Customer Personas

With your referral marketing data coming in, you can start to build customer profiles. Doing so will provide you with a good idea of your referred customer base and the different segments that compose it.

Some companies use CRM systems to build their customer profiles. If you want a more accessible option, there are referral customer persona tools available to you. These kinds of tools do require more manual data entry. However, they still allow you to organize and store your data for the long term. Smaller companies tend to benefit more from manual data entry.

Remember that this step should be adaptable. Your customers are real people with changing interests and demands. If you use the tools at your disposal, you will be able to keep them satisfied and increase the number of sales your company closes.

Related Information: “Top Sources of referral marketing traffic on the web.”

Focus on Your Loyal Customer Base

While you want to draw in new customers, you must dedicate attention to your current ones as well. Ensure no one is neglected once they’ve completed a purchase.

Use these tips to retain the interest of someone who has purchased from your company:

  • Implement a loyalty program with regular promotions
  • Thank a paying and referred customer for their business with a personalized message or small gift certificate

You can send these messages out via email, which you should’ve collected during the customers’ ordering process. If you have no way of contacting a customer post-purchase, create a way for you to do so in the future.

Related Information: “Pinterest will boost your referral traffic, but can it boost sales.”

3) Collaborate with Other Marketing Departments in Your Company

Don’t isolate your data-driven marketing strategy in its own bubble. This method needs to be maintained and understood by every marketing department in your entire company. As a marketer, you must communicate your approach to all marketing departments in your business.

With that in mind, be sure to monitor referral marketing industry changes that are taking place. Staff members from other marketing departments can be a big help when keeping up with the latest trends in your industry.

4) Measure Your Progress

A data-driven marketing approach that works one year may fail miserably in the next one. So always keep an eye on your referral marketing strategy. Be honest about what is and isn’t working. Track your referral marketing KPIs. Don’t ignore an influx of new referred customer data. It could be just what you need to make positive changes to your company’s operations and reputation.

Two Examples of Data-Driven Referral Marketing

The above outline can help you get started with building a data-driven referral marketing plan of your own. In addition, it may be helpful to view two real-world examples of data-driven referral marketing:

1) Update Your Messaging

Some companies fall victim to using decorative language in their referral advertising, alienating a mass and potential audience. For example, if you’re trying to market your referral software to a specific audience, avoid long taglines on your company’s home page:

  • We implement an integrated computing framework to create more profitable referral and client relationships.

Instead, opt for something simpler that still conveys meaning:

  • For example, our software cuts your scheduling time in half.

I went ahead and spoke to Kirsty McAdam, the CEO of global referral software leader, Referral Factory. She advised every referral marketer to update their message by collecting information about their audience. This information will include:

  • How this person discovered your company
  • What the customer likes and dislikes about your software
  • What made the individual decide to buy your product?
  • What they were using before they bought your software

According to Kirsty McAdam of Referral Factory, Collecting this kind of referral marketing data will help you better tailor a referral marketing message that captures the attention of new and returning referral customers.

2) Retargeting

Retargeting is an extremely effective data-driven marketing strategy. It involves displaying your referral marketing adverts to customers as they make purchases from or casually browse different, unrelated websites.

With retargeting, you can even get the attention of potential customers who have made their way to a competing website. It improves your brand’s visibility. It can also push an indecisive customer to secure a final sale with your company. To get started, you will inevitably need more than one referral marketing channel.

For example, if you advertise your housecleaning service on Facebook and Twitter, you can seek out customers who have been searching for this particular service via other mediums. If they have been performing web research over the past several days, they will start to see ads targeted towards them on social media.

You can set up specific retargeting campaigns through platforms like Facebook, LinkedIn, and Twitter. Another option is using third-party platforms that specialize in web and social retargeting. Either way, this method allows you to increase brand awareness and skyrocket conversions.

Data-Driven Marketing Success and Outlook

As a digital marketer, you should be excited about the future of data-driven marketing. It has been the driving force in many successful marketing campaigns and will only inform more and more of our marketing efforts.

A data-driven referral marketing approach works wonders for new and established companies alike with the right tools and knowledge. Here is some other related information I wrote in my blog:  I believe the information I give you in this post will increase your ROI, help you close more sales, and allow you to create more meaningful connections with new and recurrent customers.

Image Credit: collis; pexels; thank you!

Ekalavya Hansaj

Serial Entrepreneur, Investor, producer and Author

Founder at Quarterly Global. Entrepreneur, Investor and Producer at Criminal Wolf Music and Indie MM. Author of “How to grow your startup and small business”.

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Fintech Kennek raises $12.5M seed round to digitize lending

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Google eyed for $2 billion Anthropic deal after major Amazon play


London-based fintech startup Kennek has raised $12.5 million in seed funding to expand its lending operating system.

According to an Oct. 10 tech.eu report, the round was led by HV Capital and included participation from Dutch Founders Fund, AlbionVC, FFVC, Plug & Play Ventures, and Syndicate One. Kennek offers software-as-a-service tools to help non-bank lenders streamline their operations using open banking, open finance, and payments.

The platform aims to automate time-consuming manual tasks and consolidate fragmented data to simplify lending. Xavier De Pauw, founder of Kennek said:

“Until kennek, lenders had to devote countless hours to menial operational tasks and deal with jumbled and hard-coded data – which makes every other part of lending a headache. As former lenders ourselves, we lived and breathed these frustrations, and built kennek to make them a thing of the past.”

The company said the latest funding round was oversubscribed and closed quickly despite the challenging fundraising environment. The new capital will be used to expand Kennek’s engineering team and strengthen its market position in the UK while exploring expansion into other European markets. Barbod Namini, Partner at lead investor HV Capital, commented on the investment:

“Kennek has developed an ambitious and genuinely unique proposition which we think can be the foundation of the entire alternative lending space. […] It is a complicated market and a solution that brings together all information and stakeholders onto a single platform is highly compelling for both lenders & the ecosystem as a whole.”

The fintech lending space has grown rapidly in recent years, but many lenders still rely on legacy systems and manual processes that limit efficiency and scalability. Kennek aims to leverage open banking and data integration to provide lenders with a more streamlined, automated lending experience.

The seed funding will allow the London-based startup to continue developing its platform and expanding its team to meet demand from non-bank lenders looking to digitize operations. Kennek’s focus on the UK and Europe also comes amid rising adoption of open banking and open finance in the regions.

Featured Image Credit: Photo from Kennek.io; Thank you!

Radek Zielinski

Radek Zielinski is an experienced technology and financial journalist with a passion for cybersecurity and futurology.

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Fortune 500’s race for generative AI breakthroughs

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Deanna Ritchie


As excitement around generative AI grows, Fortune 500 companies, including Goldman Sachs, are carefully examining the possible applications of this technology. A recent survey of U.S. executives indicated that 60% believe generative AI will substantially impact their businesses in the long term. However, they anticipate a one to two-year timeframe before implementing their initial solutions. This optimism stems from the potential of generative AI to revolutionize various aspects of businesses, from enhancing customer experiences to optimizing internal processes. In the short term, companies will likely focus on pilot projects and experimentation, gradually integrating generative AI into their operations as they witness its positive influence on efficiency and profitability.

Goldman Sachs’ Cautious Approach to Implementing Generative AI

In a recent interview, Goldman Sachs CIO Marco Argenti revealed that the firm has not yet implemented any generative AI use cases. Instead, the company focuses on experimentation and setting high standards before adopting the technology. Argenti recognized the desire for outcomes in areas like developer and operational efficiency but emphasized ensuring precision before putting experimental AI use cases into production.

According to Argenti, striking the right balance between driving innovation and maintaining accuracy is crucial for successfully integrating generative AI within the firm. Goldman Sachs intends to continue exploring this emerging technology’s potential benefits and applications while diligently assessing risks to ensure it meets the company’s stringent quality standards.

One possible application for Goldman Sachs is in software development, where the company has observed a 20-40% productivity increase during its trials. The goal is for 1,000 developers to utilize generative AI tools by year’s end. However, Argenti emphasized that a well-defined expectation of return on investment is necessary before fully integrating generative AI into production.

To achieve this, the company plans to implement a systematic and strategic approach to adopting generative AI, ensuring that it complements and enhances the skills of its developers. Additionally, Goldman Sachs intends to evaluate the long-term impact of generative AI on their software development processes and the overall quality of the applications being developed.

Goldman Sachs’ approach to AI implementation goes beyond merely executing models. The firm has created a platform encompassing technical, legal, and compliance assessments to filter out improper content and keep track of all interactions. This comprehensive system ensures seamless integration of artificial intelligence in operations while adhering to regulatory standards and maintaining client confidentiality. Moreover, the platform continuously improves and adapts its algorithms, allowing Goldman Sachs to stay at the forefront of technology and offer its clients the most efficient and secure services.

Featured Image Credit: Photo by Google DeepMind; Pexels; Thank you!

Deanna Ritchie

Managing Editor at ReadWrite

Deanna is the Managing Editor at ReadWrite. Previously she worked as the Editor in Chief for Startup Grind and has over 20+ years of experience in content management and content development.

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UK seizes web3 opportunity simplifying crypto regulations

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Deanna Ritchie


As Web3 companies increasingly consider leaving the United States due to regulatory ambiguity, the United Kingdom must simplify its cryptocurrency regulations to attract these businesses. The conservative think tank Policy Exchange recently released a report detailing ten suggestions for improving Web3 regulation in the country. Among the recommendations are reducing liability for token holders in decentralized autonomous organizations (DAOs) and encouraging the Financial Conduct Authority (FCA) to adopt alternative Know Your Customer (KYC) methodologies, such as digital identities and blockchain analytics tools. These suggestions aim to position the UK as a hub for Web3 innovation and attract blockchain-based businesses looking for a more conducive regulatory environment.

Streamlining Cryptocurrency Regulations for Innovation

To make it easier for emerging Web3 companies to navigate existing legal frameworks and contribute to the UK’s digital economy growth, the government must streamline cryptocurrency regulations and adopt forward-looking approaches. By making the regulatory landscape clear and straightforward, the UK can create an environment that fosters innovation, growth, and competitiveness in the global fintech industry.

The Policy Exchange report also recommends not weakening self-hosted wallets or treating proof-of-stake (PoS) services as financial services. This approach aims to protect the fundamental principles of decentralization and user autonomy while strongly emphasizing security and regulatory compliance. By doing so, the UK can nurture an environment that encourages innovation and the continued growth of blockchain technology.

Despite recent strict measures by UK authorities, such as His Majesty’s Treasury and the FCA, toward the digital assets sector, the proposed changes in the Policy Exchange report strive to make the UK a more attractive location for Web3 enterprises. By adopting these suggestions, the UK can demonstrate its commitment to fostering innovation in the rapidly evolving blockchain and cryptocurrency industries while ensuring a robust and transparent regulatory environment.

The ongoing uncertainty surrounding cryptocurrency regulations in various countries has prompted Web3 companies to explore alternative jurisdictions with more precise legal frameworks. As the United States grapples with regulatory ambiguity, the United Kingdom can position itself as a hub for Web3 innovation by simplifying and streamlining its cryptocurrency regulations.

Featured Image Credit: Photo by Jonathan Borba; Pexels; Thank you!

Deanna Ritchie

Managing Editor at ReadWrite

Deanna is the Managing Editor at ReadWrite. Previously she worked as the Editor in Chief for Startup Grind and has over 20+ years of experience in content management and content development.

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