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How Snowflake's Real-time Attribution Modeling Boosts Marketing Outcomes

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Sigma Solve
How Snowflake's Real-time Attribution Modeling Boosts Marketing Outcomes

Synopsis:

Do your marketing campaigns accurately reach your target audience? Is your marketing team able to generate many actionable leads and conversions? If the answer is negative, you should reevaluate your fundamental marketing efforts, allowing data to take center stage and snowflake analytics tools to do the heavy lifting. Usually, businesses are advised to build a unified data architecture to enable the marketing teams to make sense of the data and reach their target audiences accurately.


In this blog, we will evaluate how a cloud-based data analytics platform, Snowflake, helps businesses decipher data and facilitate the power of data analytics. We will observe the performance of Snowflake’s real-time attribution modeling and assess its worth, providing a decisive edge to businesses over their competitors with Snowflake cloud consulting services.


Background:

Business dynamics have been on the move ever since digitization made its way to the boardrooms. Traditional marketing paradigms have been thrown out the window since data started making accurate sense of customers’ preferences, behaviors, journeys, and experiences. To revolutionize data analytics, Snowflake cloud solutions started providing a multi-touch attribution mechanism to meet marketing necessities in real-time.

As a result, businesses are empowered to adopt dynamic marketing strategies to boost marketing outcomes. As we dive deeper, we will inspect the capabilities, benefits, and core features of Snowflake’s multi-point attribution process.


Understanding Attribution Modeling


Attribution Modeling — Nuancing Around Consumer Data

What the neutron and proton are to a nucleus, Return on investment and Customer Experience are to businesses. Small or big, today, businesses are analyzing customers’ journeys and evaluating the data like never before. Businesses’ ability to extract the data from various touchpoints and attribute credit to each to determine the contribution of touchpoints in conversion is known as “Attribution Modeling”.


When marketing reaches the cloud, businesses are assured of accomplishing their objectives. Being able to surf an ever-increasing pool of data and decode it accurately to build nuance wins the race. Developing an efficient data model that enables businesses to make real-time decisions to provide a personalized customer experience helps businesses overcome competition-generated hurdles.


Why Attribution Modeling? — Importance

Earlier businesses were satisfied with conversions by the sales or digital marketing

 team; however, gone are the days. Nowadays, accounting for actionable leads and conversion isn’t enough; businesses want to know which channel generated the maximum leads and which touchpoint made the maximum impact.


From an investment point of view, businesses must identify what motivates them the most among all the channels and touchpoints — SEO, Paid advertising, or email campaigns.


Traditional Attribution Models — Impractical and Inadequate

First-Touch Attribution, Last-Touch Attribution, Linear Attribution, Time-Decay attribution, etc., are some traditional attribution models. Understanding traditional attribution models to understand marketing fundamentals may still make sense. However, they are no longer practical for enhancing customer experiences or driving sales. Traditional models were rule-based, so they failed to identify consumers’ complex and intrinsic journeys to understand the impact points.

  • TAMs were implemented linearly and, therefore, could not solve the entangled journey of touchpoints.
  • TAMs were partial, as they leaned towards a particular set of touchpoints, ignoring the others.
  • Implementing a single-line traditional attribution model is difficult in a multi-channel marketing structure.


Real-time Attribution Modeling — Making sense instantly

As the marketing world has started revolving around data, making a real-time sense of customer data plays a vital role in businesses targeting their audience with highly focused marketing campaigns. Since the digital landscape is evolving unabated, predicting consumer behavior and evaluating the touchpoint contribution to conversion to target them and improve sales is a game changer for marketers.


Real-time Attribution Modeling is equipped to evaluate the data from a huge data repository to develop analytics that helps the marketing team understand which touchpoints and channels need more focus and funding to convert more leads into purchases. Snowflake cloud solutions use Snowflake’s data warehouse capabilities to provide consumer data analytics in real-time. An efficient cloud consulting service helps businesses develop custom attribution models using Snowflake.


Compared to traditional attribution models, which usually record the consumer journey only after its completion, marketers get to travel as customers make their way to buy a product or service. Thus, marketers become capable of addressing the reluctance or doubts of customers.


The Power of Real-time Data

How Does Snowflake’s Real-Time Attribution Modeling Work?

Data Integration: Data integration is at the core of Snowflake’s attribution modeling. It accumulates data from all touchpoints in real-time and consolidates it in a cloud data warehouse.

Data Processing: Post-consolidation, Snowflake Cloud’s data-processing framework processes the data with electrifying speed. The real-time processing of data changes the whole marketing game.

Attribution Models: Snowflake development service providers

 offer various Snowflake attribution models to marketers. Marketers can pick and choose models according to their objectives.

Real-Time Insights: Processing raw data into actionable insight instantly is where Snowflake is unbeatable. A real-time dashboard shows real-time campaign performance for quick decision-making.

Predictive Analytics: In sales, nothing is more worthy than the ability to predict the customer’s journey and adjust campaigns for successful conversion. Thus, Snowflake’s predictive analytics help optimize marketing campaigns.

Scalability: The cloud-based infrastructure of Snowflake is accommodating and scalable. It relieves marketers from worrying about consolidating and processing a large volume of data as sales increase and business grows.


In a nutshell, Snowflake’s real-time multi-point attribution models transform how marketers design their campaigns, target their audience, pinpoint prospective customers, resolve their doubts, and effect conversion. By leveraging Snowflake’s real-time data analytics, businesses can easily strengthen their digital transformation and empower their marketing teams to improve ROI and enhance customer journeys.


Real-time Attribution and Real-time Data — The Marketing Advantages

Data-driven analytics has changed the marketing rules for businesses forever. Although marketers need to acquire big data analytics skills, the analysis and reports generated by the real-time attribution modeling of Snowflake have added ease to marketing jobs. There are numerous advantages that marketers enjoy with real-time data analytics

.

Timely Decision-Making: With Snowflake Cloud Solutions enabling real-time data for marketers, decisions regarding campaigns and campaign interventions become timely, quick, and accurate. It allows marketers to manage the budget effectively, improving agility.

Optimized Campaign Performance: Real-time data analytics arms marketers to quickly observe and optimize campaign performance. Marketers can monitor key performance parameters in real-time to evaluate the performance of channels, campaigns, messaging, and offers and instantly adapt.

Improved Personalization: Personalization is the key, and real-time data analytics generated using attribution models ensure marketers deliver highly personalized customer experiences. Marketers can deliver customized recommendations and offers for increased engagement to improve customer satisfaction.

Enhanced Customer Engagement: Real-time data allows marketers to interact with customers almost immediately. For example, if the customer abandons the cart, a marketer can immediately send a message or email to address the reluctance and recover the lost sales opportunity.

A/B Testing and Experimentation: Recognizing and devising a winning strategy and engaging with the customer instantly for conversion is a game changer for marketers. Real-time data analytics empowers marketers to carry out A/B tests to implement changes to seal the deal at the last minute.

Fraud Detection and Prevention: Real-time data is a major deterrent against cyber fraud. As marketers, via greater conversions, they can also detect and prevent fraudulent financial transactions. Real-time insight into data allows marketers to red-flag suspicious or malicious transactions.

Cost Efficiency: Real-time data analytics gives marketers insight into channels and campaigns. Thus allowing them to allocate the budget wisely to avoid the wastage of resources on redundant campaigns. On the contrary, businesses can fund those campaigns that bring them results.

Competitive Advantage: A prospective customer cannot vie for only one business. A quick pursuit offering a personalized experience in real-time helps marketers change the customer’s mind. Marketers can win customers with real-time data who might be considering an alternative business for services or products.

Revenue Growth: Whether marketers optimize campaigns, enhance the customer experience or prevent fraud, ultimately, all these benefits result in sales. Increased sales improve revenue. Real-time data-based timely decisions enhance growth opportunities and, consequently, improve profitability.


Conclusion:

Real-time data is a marketer’s magic wand. It empowers the marketing department to make accurate decisions. It helps provide an enhanced customer experience by adapting to rapidly changing situations.

Snowflake’s real-time data analytics help marketers stay ahead of their competitors, generating more sales and improving revenue and profitability.


Sigma Solve’s cloud consulting services provide in-depth knowledge about Snowflake’s data models. Find out more about Snowflake’s cloud-based solutions and developing data models to improve business prospects.


Original source: here

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