Data is the oil businesses thrive on. Yet, the underutilization of data is a big business problem.
In a recent survey, nearly 90% of marketers admitted that data is the most underutilized asset.
Businesses are heavily investing in tools, people, and infrastructure that capture operations and customer data, but only a fraction can unlock its value, scale, and prioritize its data. As a result, they often miss out on opportunities to transform underutilized data into quantifiable returns - critical insights that deepen existing business relationships and create new services to drive revenue.
This is precisely the kind of value from data that helps firms refine marketing strategies and enhance customer experience.
Data-driven marketing enables companies to leverage data and gain a better view of customer motivations, preferences, and behaviors. This essential guide aims to share everything you need about data-driven marketing.
So, let’s get started!
What Is Data-Driven Marketing?
Data-driven marketing leverages data (customer, product, marketing, operations) from various sources to get in-depth insights into customer behavior. These insights allow marketers to predict consumer behavior and drive marketing decisions that directly impact business growth and revenue.
Leveraging data allows marketers to see what works and why. Thus, they can build effective demand-generation campaigns based on relevant metrics, allowing them to generate better quality leads and improve CX. In a recent report, 95% of B2B marketers shared that their demand gen efforts significantly improved when they leveraged data.
Thus, data-driven marketing can help marketing teams to understand the campaign performance, what emails are triggering better opens, the source converting faster, and more.
Significance of Data-Driven Marketing in SaaS
The growth of digitization has pushed SaaS firms to move towards a data-driven culture. Deriving insights from data alone can help SaaS marketers identify new business opportunities, grow sales, understand customers, and improve customer experience.
Here’s why data-driven marketing makes sense for SaaS.
- SaaS business success thrives on market agility and the rapid iteration of products. Leveraging data allows them to maintain their operational cadence with fewer missteps when making decisions.
- Demand generation can be expensive if marketers aren’t clear on tactics and channels to prioritize. Plus, not tracking how effectively the team is executing their strategies can lead to a waste of time and money.
That’s where data-driven marketing can help. It can show SaaS marketers how to allocate their budget to acquire leads. Thus, the data-driven approach improves the efficiency of demand generation.
- Conversion rate optimization (CRO) is an effective way for SaaS firms to improve their inbound lead volume. A data-driven approach can help SaaS firms understand what persuades or discourages website or app visitors from converting. Thus, they can adjust their website strategies based on data and improve conversions and revenue.
- The SaaS domain is forever changing. With data as an arsenal, SaaS firms stay agile, swiftly identify future patterns, and plan to improve their product.
- At their inception, SaaS businesses seldom have high capital requirements. Yet, the competition in this segment makes it tough to achieve profitability goals. A data-driven culture encourages marketers to operate more efficiently, enabling them to identify wasteful processes and run leaner operations.
For a SaaS business, this means diverting resources to revenue-generating activities.
Data-Driven Marketing Examples
The data-driven approach in marketing allows marketers to overcome the most complex challenges quickly and easily. They can spot new trends, identify customer pain points, anticipate their next moves, and more. All of this helps in driving up the marketing ROI.
Let’s look at a few examples/use cases of data-driven marketing for business growth and profitability.
- Creating Relevant Content
Businesses can use data to build relevant content strategies. For instance, they can analyze user data or measure their blog performance to figure out the type of content their audience consumes.
Similarly, they can use demographic data like age, gender, job, and location to reveal what their audience is interested in.
- Sharing Behavior-Triggered Emails
Most of us have experienced this in our mailboxes at some point in time. Remember when you signed up for a service and missed completing the setup? In all probability, after a few days, you will receive an email reminding you to complete the process.
That’s a behavior-triggered email to re-engage users who’ve gone cold. These emails prompt users to complete the necessary steps in the setup. They remind the recipient of the key features, allowing them to quickly reach activation. All this is based on customer behavior data.
- Improving Ad Campaigns
Deploying insights from data-based marketing, ads can be tailored to the audience’s preferences across social channels like Facebook, Twitter, or Instagram. This allows marketers to optimize their ad campaign spend, improve conversions, and enhance return on investment.
- Retargeting Site Visitors
A study reveals that 98% of website visitors don’t make a buying decision on their first visit to the website. However, this 98% are potential customers who can be converted into paying customers using retargeting backed with data-driven marketing.
Retargeting allows marketers too -
- Maintain top-of-the-mind recall among these prospective customers
- Bring them back to the website
It lets marketers display ads on third-party websites and target past website visitors. They are targeted based on their behavior.
For instance, if the visitor comes to the product page and leaves, you can display more information about the product. But, if they bounced just before signing up, you can remind them of their abandoned purchase.
- Paid Search Campaigns
Firms spend thousands of dollars in paid search campaigns that aren’t targeted enough to help them achieve their goals. Data-driven marketing, when integrated with these search campaigns, can assure you of relevance, thus driving qualified traffic to your pages. This increases lead generation and boosts conversions.
Data-Driven Marketing versus Traditional Marketing
When executed to perfection, data-driven marketing can help marketers deliver personalized and relevant content, thus significantly impacting their buying decisions. But this doesn’t mean that the traditional marketing methods have phased out.
When it comes to generating awareness, traditional marketing is quite effective. In fact, both marketing approaches aim at boosting sales and revenue. They differ in the way they go about achieving this goal.
Let’s look at this in detail.
Challenges with Traditional Marketing
Traditional marketing has a few basic challenges -
- Limited information about the audience, forcing marketers to base their decisions on their gut feeling or assumptions
- The trial and error method using broad campaigns leaves marketers waiting and hoping that they’ll get the necessary attention
- The only parameter considered here is sales. This approach doesn’t account for the factors that impact sales. For instance, it doesn’t look into new insights about the target marketing or audience.
Thus, no one can determine whether a campaign will be or was successful. The data sources (usually dated market studies) are unreliable.
A SaaS firm cannot use the ‘one-size-fits-all’ approach, especially when it’s targeting different types of customers - say, startups, small businesses, and enterprises. If it does, it will not be targeting these customers based on their specific needs.
It will end up spending huge amounts of money on broad campaigns with no idea about how each of them will contribute to the revenue.
With data-driven marketing, there’s no guesswork. Thus, the campaigns introduced are based on specific audience needs, preferences, demographics, behavior, buying patterns, interests, and more. Such campaigns are more relevant, with each yielding finer customer data that can be used to tweak future campaigns.
Benefits of Data-Driven Marketing
Effective SaaS marketing is impossible if it doesn’t leverage customer data. Customer behavior needs to be traced across channels - social, search ads, websites, mobile apps, and more. If that’s not done, it’s tough to understand the marketing funnel and develop strategies that convert.
Let’s look at the benefits data-driven marketing offers to businesses.
- Offers a Clear Understanding of the Target Audience
A McKinsey report reveals that personalized customer experience boosts conversion rate by 10-15%.
Data-driven marketing offers detailed insights into the audience’s interests, the websites they visit, the brands they follow, and what they search for online. The marketer gets a sound understanding of what customers prefer and where they go to find that information.
Moreover, with each interaction, marketers get access to customer behavior through the buying process.
Such insights can be leveraged to target relevant channels, fine-tune marketing communications, and improve customer experience. A good understanding of the audience helps with -
- Accurate personalization - With data-driven marketing, you can be confident that your brand messaging is relevant and consistent with customer preferences.
For instance, if you see repeated views by a prospect on your landing page, you can gauge a possible intent to buy the service. Thus, you can email them a personalized offer to nudge them to make the decision.
- Well-defined targeting - Customers prefer ads tailored to their interests. Data-driven marketing uses customer data to optimize campaign targeting and performance.
For instance, with machine learning algorithms, customer data can be assessed to learn about the relevant places to display ads.
- Attracting qualified leads
The quality of leads you attract always wins over the number. To attract such leads and set up a cash flow, it’s important to understand the target market.
Data-driven marketing offers insights into what customers are looking for, points to the potential loopholes in the strategy, and presents fitting solutions. This allows marketers to attract highly qualified leads who are ready to convert.
- Improving customer satisfaction
With data-driven marketing, businesses learn about their existing customers and prospects and tailor strategies to their needs. This not just boosts conversions and revenue but also improves customer satisfaction and loyalty.
- Creates a Seamless Omnichannel Experience
A McKinsey report reveals that personalization across physical and digital channels can achieve up to a 15% revenue increase across the customer base. The most successful firms focus on improving their omnichannel experience - personalization across online and offline journeys together.
Data-driven marketing allows marketers to monitor cross-channel data. Hence, they can trace the customer journey and offer customers an omnichannel experience when transitioning from digital to physical and back.
Most firms implementing data-driven marketing discover that their leads come from 2 or 3 channels. In such cases, omnichannel optimization ensures sensible budget allocation and prioritization, allowing maximum ROI.
- Allows Strategic Decision Making
Through data-driven marketing, marketers have access to actionable data that relates to the customer’s likes, dislikes, online behavior, engagement, and more. Thus they can predict how customers will react to specific brand messaging and make strategic CX decisions.
The decision-making process is also faster, enabling marketers to discard what’s not working or needs optimization.
- Informs the Product Development Team
Data-driven marketing decisions are based on customer and market insights. Hence, it supports businesses in developing relevant products that customers need. This hugely reduces the chances of product failure.
The actionable user data is critical for decisions regarding the features and functionalities that customers love. Whether it’s a SaaS software platform or an application, data-driven marketing insights allow marketers to come up with solutions that customers prefer. This hugely contributes to customer satisfaction.
- Paves the Path for Marketing Automation
A SaaS marketer is constantly overwhelmed by the sheer volume of data collected across various platforms.
Not all of this data is useful.
So, getting the data together, segregating the useful part, and analyzing it is pretty challenging. Data-driven marketing is all about extracting actionable insights from large data sets to predict the future. This paves the path for marketing automation and algorithmic advertising.
By leveraging the right marketing automation tools, converting insights into marketing tasks and workflows is straightforward. Marketing automation has a significant impact on the ROI, making it easy for marketers to account for every dollar spent.
- Powers Your Cross-Selling and Up-Selling Tactics
Data-based marketing offers rare insights that help marketers move their prospects quickly through the funnel. This makes the entire customer-acquisition process cost-efficient.
Besides, it offers cross-selling and up-selling opportunities through the funnel, boosting the revenue per customer. Once the customer purchases a solution, marketers can offer relevant solutions to keep them engaged after the sales process. Thus, customers stay loyal and make more purchases in the future.
- Improves Marketing ROI
When marketers use customer data to power their business decisions, their campaign performance is optimized across channels while ensuring attribution accuracy. They can determine the channels returning the most revenue at low spending. It also helps in making improved and accurate predictions, allowing them to plan their resources optimally.
All this improves the marketing return on investment.
What Makes Data-Driven Marketing Better Than Traditional Marketing
Successful SaaS marketing involves understanding customer pain points and creating a demand for the product people However, this process involves a lot of experimentation.
With traditional marketing techniques, this trial and error are based on assumptions developed about the target audience. This wastes time and resources as marketers are forced to launch multiple campaigns to identify which one meets their business objectives.
On the other hand, data-driven marketing allows marketers to gain an in-depth understanding of the target audience and present relevant offerings to the right audience at the right time and on the right channel. With detailed customer data and insights at their disposal, they can create highly-targeted and personalized campaigns highly-targeted and personalized campaigns, thus powering their customer acquisition efforts.
Does This Mean the End of Traditional Marketing?
The short answer - No!
Traditional marketing has a solid place when it comes to top-of-the-funnel marketing that aims to build brand awareness. It is ideal for brands when they enter new markets or target a new customer segment. It is effective when the objective is to increase brand reach and recognition.
Data-driven marketing is ideal for middle and bottom-of-the-funnel campaigns when brands need to nurture qualified leads to get them lower in the funnel and make a purchase decision.
Thus, both these methods can be applied in SaaS marketing depending on the stage of the funnel the customer is in.
Challenges with Data-Driven Marketing
A Gartner study reveals that going forward, marketers expect a majority of decisions to be data-driven; yet, marketing analytics influences only half of the business decisions. The study shares that data management is a top barrier to marketing analytics influence.
Another study reported poor data use and accessibility, poor data quality, and poor database integration as the top barriers to successful marketing data management.
Let’s look at a few challenges tied to data-driven marketing.
- Collecting/ Managing Massive Volumes of Data
SaaS businesses generate a lot of daily data. However, as mentioned earlier, not all this data is useful. A huge chunk of marketing data is a mess, making it tough to convert them into actionable insights. It’s only ‘clean’ data that can be used as a basis for decision-making.
More data often means high processing and storing costs for businesses. Add to this the responsibility of securing it.
In the absence of the right tools, managing data can be tough for marketers.
- Unifying or Normalizing Data/ Breaking Data Silos
Data on different channels is different. Plus, it’s stored in different locations and systems. This often creates data silos - large volumes of data lying in places with restricted interoperability and accessibility. Though these silos keep data safe, accessing it is a daunting task for marketers.
The challenge lies in unifying or normalizing this data to generate useful insights. Unifying and systemizing data is key to avoiding such silos and making sense of data.
- Interpreting Data
Collecting data on one platform is good. But knowing what it exactly means is what determines its value. Most tools, like business intelligence platforms, merely offer a visual representation of the data. They aren’t powered by the right technology to fetch meaningful insights from data.
For this, you need advanced analytics tools that can help in a quick and informed decision-making process. You need a platform like Revlitix that’s powered by predictive and prescriptive analytics to help you understand which campaigns impact customers and revenue the most.
The platform transforms raw data into digestible and actionable steps for streamlining and optimizing business processes. It also offers recommendations and the next-best actions to steer your business toward revenue goals.
- Privacy Concerns
Data privacy laws are rampant across the globe, restricting the collection, storage, and handling of customer data without consent. Thus, businesses must be extra cautious and take adequate measures to ensure they ethically collect and use customer data.
How Marketers Can Address These Data Challenges to Drive Growth?
To overcome the challenges shared above, you need to count on tools that get all the data you need to a central location, enabling you to experience the benefits of data-driven marketing.
Revlitix, our all-in-one revenue marketing platform for data-driven marketing, allows marketers to effortlessly automate all aspects of marketing analytics and make data-driven decisions each day.
Revlitix can -
- Effortlessly connect with data sources in less than 3 clicks and offer more actionable insights than any other dashboard
- Help with unifying/ normalizing and crunching data to reveal real-time insights that marketers can use in their decision making
- Crunch data effectively and apply predictive and prescriptive analytics to offer insights and next-best actions
4 Pillars of a Data-Driven Marketing Strategy
Let’s look at the building blocks of a successful data-driven marketing strategy.
The complexity and variety of data produced by SaaS businesses demand efficient and cost-effective data analytics solutions. Thus, automation is a key aspect of data-driven decision making.
Automation allows effortless uploading, handling, and processing of data using automated technologies rather than manually processing it.
The process collects, transforms, stores, and analyses data using intelligent processes, infrastructure, and machine learning, thereby evading the need for human intervention. Automation also reduces errors by ensuring that the colossal volumes of data is is loaded in a structured fashion.
- Clarity on ICP
Wasting money sucks! That’s where ICP or ideal customer profile becomes a key aspect of data-driven strategy. Studying the unique characteristics of ideal customers make it easy for marketers to cut the clutter and build razor-sharp campaigns for qualified prospects who are ready to convert.
Getting clarity in ICP allows marketers to go beyond intuition and inherent bias and use algorithms to analyze data.
Devising ICP involves -
- Predictive analytics that identifies behavioral patterns in data and transforms them into intelligence that segregates high-quality leads from low-quality.
- Quality data that powers analytics engine and AI models.
- Campaign Monitoring
Campaign monitoring involves tracking relevant performance metrics and identifying areas that need improvement.
For instance, if your business is running a social ad, monitoring its performance will help you understand why it’s performing well or underperforming. The factors influencing its performance could be the target audience, ad creative, or ad placement.
Armed with such insights, you can refine your target audience and make your campaign more effective while reducing the marketing costs involved. Such insights also reveal new audiences that could have similar needs, thus allowing you to expand your reach.
- Competitor Tracking
Monitoring competitors allows you to see regional trends and make informed decisions on planned expansions. From the top players to the up-and-comers who might introduce a new twist to a product, your competition can hugely impact your sales, business operations, and the market.
Data on competitor moves, pricing, and funding and acquisitions feed competitor analysis, enabling marketers to revise their business plans and adapt to industry trends. Here are a few competitor data points every business should track -
- Recent acquisitions and investments in technology
- Investors helping the firm scale
- Funding stages (an indicator of how they are scaling)
- News mentions to stay updated on their positioning, popularity, direction, or product changes
Implementing Data-Driven Marketing for Your SaaS
The C-suite in most companies, views the marketing department as a cost-center. This makes it critical to apply data-driven marketing to analyze which part of the budget is being aptly invested for generating revenue and which part goes into the abyss.
The C-suite wants to see numbers and this data-driven approach will help marketers prove that their efforts are having an impact on the revenue.
Let’s look at the steps you need to go through to configure a data-driven marketing approach.
- Data Collection
When SaaS buyers or prospects interact with a brand, new touchpoints appear - offline and online. This generates data at each stage of the customer journey.
Automated data collection can help in bringing data from various channels to a common location faster and with more accuracy. To begin this process, you need to -
- Define your data sources - advertising, CRM, website, and mobile applications
- Set up the data collection process
It’s critical to get all the data on a central platform as this will enable you to create cohesive buyer journeys across various channels and touchpoints. It allows you to offer consistent and relevant customer experiences and brand messaging.
The data collected should be cleansed, sorted, and organized so that advanced analytics tools can read it and offer insights. This includes removing irrelevant data, deleting anomalies, eliminating duplicate entries, and more.
- Data Processing/ Analysis
Gathering data on one platform is just the beginning. Next, the data needs to be processed in the data storage and analyzed to derive actionable insights. The data needs to work for marketers, enabling them to build reports that improve work efficiency.
Further, at this stage, they need to take care to avoid complicated solutions. The more data generated, the more complex the system tends to be. This makes it tough to spot and correct errors. Plus, these systems often demand significant resources and specialists.
An ideal solution is to choose a service that caters to all your needs - processes and analyzes data, builds marketing ROI dashboards and reports, and offers actionable insights and recommendations.
- Hypothesis Testing
Now comes the stage of data usage. In other words, the data needs to be applied to improve the marketing strategy and its impact on revenue.
The insights derived from data inform the marketer about things like whether the campaigns are performing well or which part of the funnel is the narrowest. This data tracking and analysis allows them to test various hypotheses, thus offering an opportunity to improve conversions and revenue.
Here are a few examples of hypothesis testing.
- Improving customer segments - by profitability, behavior, or conversions
- Promoting services that may interest a specific segment of customers
- Sending automated emails in response to specific customer actions
- Performance Assessment
Generating consistent revenue is the primary goal of every SaaS business. Hence, evaluating the performance on a regular basis becomes critical. This is not possible in the absence of quality data and regular reports.
Performance assessment depends on the business goals and the parameters set for defining success. One of the most straightforward ways to monitor this is by tracking critical business metrics using automated dashboards.
Check out how Revlitix allows the marketing team to track key business metrics.
The Data-Driven Marketing Tech Stack
Criteria to Build an Appropriate Solutions Stack
To build a functioning and efficient data ecosystem, you should ensure that the tool you choose works in the same infrastructure. It should effortlessly integrate with various data sources.
- Data collection/ processing capabilities
An ideal platform should be able to manage huge volumes of data, track data quality, stitch it together, spot and report errors, and automatically merge and transfer data.
- Ease of use
The service you choose should be easy to use. Your marketing team should be able to work on it without the need for technical experts.
Make sure you compare the price of the service you choose with the others available in the market. Check out the prices, features, and functionality of the services, and choose the one that meets your needs.
Data-Driven Marketing Tools
Stitching and crunching data quickly and efficiently to get actionable insights and recommendations is the surefire way to power your marketing initiatives and boost revenue. However, for achieving this, you need a fitting data-driven marketing tech stack.
For long, businesses have relied on conventional business intelligence tools to make sense of data. However, SaaS businesses are generating colossal volumes of data that need to be brought together, crunched, and analyzed at scale.
They need advanced analytics tools that sit atop these conventional ones and help them be self-sufficient enough to apply advanced analytics quickly.
They need Revlitix.
The only data-driven marketing tool that automates advanced analytics
The only platform that offers the shortest path from gut feelings to data-driven decisions
- Allows you to build relevant dashboards. These are built and vetted by experts with > 15 years of experience.
- Offers 100+ pre-designed, drag-and-drop dashboards with a 30-second set-up - Not kidding!
- Effortlessly integrates with key Martech platforms, thus streamlining business operations and improving the efficiency of data management.
- Saves you the effort involved in coding. You don’t have to write a single line of code. Unlike other solutions, Revlitix is a no-code platform, not low code.
Revlitix offers a visual and intuitive platform that’s perfect for SaaS marketers. The revenue analytics software connects data with insights and turns them into the next-best actions.
The revenueOS meets every SaaS marketer’s needs.
- It detects performance anomalies before it's too late
- It collaborates with the team
- It builds out-of-the-box and impressive dashboards
- It uses custom playbooks to reduce time to action
Before We Conclude: Bonus! Upcoming Data-Driven Marketing Trends
Data is the new currency in the business world that has transformed marketing and overall operations. Because marketers have more data about their customers at their fingertips, technologies, trends, and regulations are constantly evolving and progressing. This poses several opportunities and risks to businesses.
We are sharing a few upcoming data-driven marketing trends that you should consider when forming your marketing strategy.
- Predictive and Prescriptive Analytics Are Keeping Marketers Agile
SaaS marketers are striving to keep pace with the constantly changing customer behavior and preferences. In such a scenario, AI-powered predictive and prescriptive analytics is enabling marketers to build agile data models.
These technologies are helping them stay on top of existing behavior, predict future trends, and proactively plan strategies. Moreover, prescriptive analytics suggests a necessary course of action that goes beyond mere explanations or predictions.
For instance, product managers usually rely on data models for performing market research, testing minimum viable products (MVPs), and collecting behavioral customer data. Prescriptive analytical models identify buying trends to predict which features are most relevant to the marketplace. This information is critical for product lifecycle management as it helps in refining the UX of the product.
In fact, the predictive and prescriptive analytics market is expected to register a CAGR of 24% between 2018-2028. These advanced analytics solutions powered by ML, algorithms, and computational modeling are helping marketers address issues using statistical approaches and making them more agile in the process.
A common misconception is that the predictive and prescriptive analytics industry is dominated by tech giants like Microsoft and IBM. However, alongside these big brands are specialized and advanced analytics platforms like Revlitix that are geared around no-code for simplicity and speed.
Revlitix is powered by predictive and prescriptive analytics as it can define, create, and execute recommendations based on past business performance. It’s based on ML algorithms that generate actionable insights within seconds. Data engineering stitches the data from various platforms while its data science and learning models interpret data and offer relevant insights and recommendations.
- AI/ML Improving Personalization
AI and ML allow the effortless conversion of massive volumes of data into comprehensive information within seconds. This is something impossible for humans.
AI-driven personalization is leveraging machine learning, deep learning, natural language processing, and more to redefine how brands interact with customers. These technologies are making it possible for marketers to offer personalized real-time engagement at scale.
Using ML algorithms marketers can teach AI-based systems to automatically learn from existing data and improve with time. Further, AI modeling techniques and ML algorithms are offering insights that cut down human error often leading to a campaign misfire. While we still need humans to refine insights provided by technology, there’s no limit to the kind of data these technologies provide at scale.
- Growing Privacy Concerns Require Marketers to Rely on Their Data
Data breaches have been on the rise over the past decade. And unfortunately, this trend isn’t slowing down.
This scenario is leaving customers anxious about how their data is used. In fact, data privacy regulations, such as GDPR, CCPA, and HIPAA require marketers to exhibit transparency when using customer data.
Top brands like Google and Microsoft have already taken the necessary measures to address this concern. They have announced the removal of third-party cookies from websites.
This poses a challenge for businesses extensively using website cookies to power their personalization tactics. As these privacy and security regulations become more prevalent, marketers must rely on their data instead of third-party sources. This requires them to enhance their tech stack to perform future-ready data-driven marketing.
- A Boost in Data-Sharing Capabilities
Unless it is confidential, customer data should be made accessible to all. Improved data-sharing capabilities are increasing visibility into the customer journey across teams. This breaks data silos and helps in building comprehensive and connected data-driven strategies that can benefit all stakeholders.
The key to effective SaaS marketing is making the customer feel that their pain points are being addressed and engaging them through a personalized conversation. Businesses need to connect with them and make them feel ‘not like they are being marketed to.’
By adopting the data-driven marketing approach, SaaS marketers can achieve this. They can build a customer-centric strategy that appeals to the audience and pushes them to lower into the marketing funnel.
The easy adoption of technologies like AI and ML is only making the foundation stronger for data-driven marketing. It’s time SaaS marketers adopt it in their marketing processes before it’s too late.
Frequently Asked Questions (FAQs)
1. What is data-driven marketing?
Data-driven marketing is a marketing model that centers around customer and market data. In this form of marketing, business decisions are based on the data collected and analyzed.
To begin with data-driven marketing, marketers set up a suitable system for tracking, collecting, and storing data safely. For real-time monitoring and reporting, they use advanced tools that integrate data from various sources and process it to come up with actionable insights. These insights enable them to make informed and data-driven marketing decisions.
2. Why is data-driven marketing important for SaaS?
Data-driven marketing is a significant marketing approach SaaS firms must apply to yield impressive results and boost conversions and revenue. A lot of data is generated from SaaS purchases and processing/ analyzing this data can help marketers make better decisions, avoid mistakes, and ensure better outcomes from their investments.
3. How does data-driven marketing work?
Marketers study the impact of their efforts on customers and revenue, thus yielding a significant amount of data. This analyzed data and the insights derived are used to optimize communications with specific audience segments.
Customer, financial, and operational data are used to reveal information related to audience attitudes, upcoming trends, performance statistics, transactions, and more. Such insights can help marketers to optimize processes, automate functions, save costs, and improve revenue and data-driven marketing growth.