Predictive Lead Scoring

19Aug

Salesforce Data Snowflake and You

Unlock the Full Potential of Your Salesforce Data with Snowflake At Tectonic, we’ve dedicated years to helping businesses maximize their Salesforce investment, driving growth and enhancing customer experiences. Now, we’re expanding those capabilities by integrating with Snowflake.Imagine the power of merging Salesforce data with other sources, gaining deeper insights, and making smarter decisions—without the hassle of complex infrastructure. Snowflake brings this to life with a flexible, scalable solution for unifying your data ecosystem.In this insight, we’ll cover why Snowflake is essential for Salesforce users, how seamlessly it integrates, and why Tectonic is the ideal partner to help you leverage its full potential. Why Snowflake Matters for Salesforce Users Salesforce excels at managing customer relationships, but businesses today need data from multiple sources—e-commerce, marketing platforms, ERP systems, and more. That’s where Snowflake shines. With Snowflake, you can unify these data sources, enrich your Salesforce data, and turn it into actionable insights. Say goodbye to silos and blind spots. Snowflake is easy to set up, scales effortlessly, and integrates seamlessly with Salesforce, making it ideal for enhancing CRM data across various business functions.The Power of Snowflake for Salesforce Users Seamless Data IntegrationSnowflake’s cloud-native architecture lets you combine structured, semi-structured, and unstructured data effortlessly. Salesforce users can extend their data capabilities by integrating insights from external sources, such as web analytics, other CRMs, or real-time IoT data, all while keeping the setup simple. This provides a comprehensive view of each customer and enables faster, data-driven decisions. Scalability without ComplexitySnowflake is a fully managed, cloud-native platform that scales to meet your growing data needs without heavy infrastructure demands. This allows Salesforce users to expand their data strategy without altering their CRM setup or adding IT resources. Advanced Analytics and AI/ML ReadinessFrom predictive lead scoring to customer churn analysis, Snowflake supports AI and machine learning workloads, enabling Salesforce users to develop models that deliver actionable insights. By unifying data across platforms, Snowflake allows for more accurate and robust AI/ML models, driving smarter decisions across areas like customer support and product recommendations. Enterprise-Grade Security & GovernanceSnowflake ensures that your data is secure and compliant. With top-tier security and data governance tools, your customer data remains protected and meets regulatory requirements across platforms, seamlessly integrating with Salesforce. Cross-Cloud Data SharingSnowflake’s Snowgrid feature makes it easy for Salesforce users to share and collaborate on data across clouds. Teams across marketing, sales, and operations can access the same up-to-date information, leading to better collaboration and faster, more informed decisions. Real-Time Data ActivationCombine Snowflake’s data platform with Salesforce Data Cloud to activate insights in real-time, enabling enriched customer experiences through dynamic insights from web interactions, purchase history, and service touchpoints. Tectonic + Snowflake: Elevating Your Salesforce Experience Snowflake offers powerful data capabilities, but effective integration is key to realizing its full potential—and that’s where Tectonic excels. Our expertise in Salesforce, now combined with Snowflake, ensures that businesses can maximize their data strategies. How Tectonic Helps: Strategic Integration Planning: We assess your current data ecosystem and design a seamless integration between Salesforce and Snowflake to unify data without disrupting operations. Custom Data Solutions: From real-time dashboards to data enrichment workflows, we create solutions tailored to your business needs. Ongoing Support and Optimization: Tectonic provides continuous support, adapting your Snowflake integration to meet evolving data needs and business strategies. Real-World Applications Retail: Integrate in-store and e-commerce sales data with Salesforce for real-time customer insights. Healthcare: Unify patient data from wearables, EMRs, and support interactions for a holistic customer care experience. Financial Services: Enhance Salesforce data with third-party risk assessments, enabling quicker, more accurate underwriting. Looking Ahead: The Tectonic Advantage Snowflake opens up new possibilities for Salesforce-powered businesses. Effective integration, however, requires strategic planning and hands-on expertise. Tectonic has a long-standing track record of helping clients get the most out of Salesforce, and now, Snowflake adds an extra dimension to our toolkit. Whether you want to better manage data, unlock insights, or enhance AI initiatives, Tectonic’s combined Salesforce and Snowflake expertise ensures you’ll harness the best of both worlds. Stay tuned as we dive deeper into Snowflake’s features, such as Interoperable Storage, Elastic Compute, and Cortex AI with Arctic, and explore how Tectonic is helping businesses unlock the future of data and AI. Ready to talk about how Snowflake and Salesforce can transform your business? Contact Tectonic today! Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

August 19, 2024in Data, Enterprise, Salesforce, Salesforce Data Cloud, Snowflake

11Apr

Traditional lead scoring relies on predefined criteria and subjective assumptions, whereas predictive lead scoring (PLS) harnesses machine learning algorithms to analyze extensive data and identify key predictors of lead quality. Traditional lead scoring only learns from data if you revise your scoring methodology for it. Predictive lead scoring constantly reworks the machine learning model based on more and newer data. Traditional lead scoring can be impacted by human error and bias. PLS analyzes from historical data eliminating bias and error. PLS employs a machine learning model to assign scores to open leads based on historical data, enabling sales teams to prioritize effectively and improve lead qualification rates while reducing the time spent on lead qualification. Discover how AI can elevate PLS to new heights and transform various organizational functions amidst shrinking budgets and heightened performance expectations across sales and marketing teams. Key Benefits of Predictive Lead Scoring: PLS leverages data science and machine learning to analyze and predict future outcomes based on historical and current data, guiding businesses in identifying high-potential leads and optimizing resource allocation. Implementing Predictive Lead Scoring: AI CRM and PLS: AI-enabled CRM platforms like Salesforce’s Einstein Lead Scoring automate lead scoring processes, leveraging extensive data to predict lead quality and prioritize effectively for sales and marketing teams. Benefits of Predictive Lead Scoring: AI and Machine Learning in Lead Scoring: AI and machine learning enhance lead scoring by analyzing vast data sets, identifying patterns, and predicting behaviors for more accurate lead qualification and prioritization. A data-driven enterprise is a smarter enterprise acting on data and insights. Salesforce’s Intelligent Lead Scoring: Salesforce’s Einstein Lead Scoring automates lead scoring processes within Sales Cloud and Marketing Cloud, providing tailored metrics and insights for informed decision-making. Generative AI and Predictive Lead Scoring: Generative AI streamlines processes like email personalization and content creation, enhancing marketing effectiveness and productivity. Good PLS with AI and machine learning transforms lead management by leveraging data insights for efficient and accurate lead qualification, ultimately driving improved sales and marketing performance. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

April 11, 2024in Einstein Insights

22Jul

Marketing Cloud Lead Scoring

The acquisition of Exacttarget, now known as Salesforce Marketing Cloud, in 2012 caused a stir in the industry. It wasn’t due to Salesforce’s reputation for acquiring top martech products and teams, but rather because Salesforce had predominantly focused on B2B2B, while Exacttarget was firmly established in the B2C realm. Nonetheless, the acquisition also brought in Pardot, one of the leading marketing automation platforms for B2B marketing at that time. So, why did Salesforce make this move? They recognized that B2C-style marketing was on the verge of becoming the norm in B2B environments. This approach emphasizes storytelling and creating experiences over simple transactions. Salesforce Marketing Cloud enriches email journeys with SMS, advertising, social engagement, and more. Today, it ranks among the top three choices for enterprises, counting clients like Adidas and American Express among its roster. However, like any product, Marketing Cloud has its acknowledged limitations, especially when competing with Marketo, Eloqua, or Hubspot in fiercely contested deals. One significant challenge for B2B marketers is Marketing Cloud’s lead scoring and website tracking functionalities—critical tools for achieving superior sales and marketing alignment and executing client-driven, behavioral marketing campaigns. Lead scoring is a tactic used in marketing and sales to prioritize potential customers (leads) based on their likelihood to convert into paying customers. The aim is to focus the sales team’s efforts on leads most likely to convert, thereby enhancing the efficiency of the sales process and maximizing revenue. Lead scoring involves assigning a numerical value or score to each lead based on various factors and behaviors indicating their level of interest and engagement with your products or services. These factors include demographics, behavioral data, engagement metrics, lead source, intent, scoring models, explicit data, and negative signals. Once leads are scored, they can be categorized into different segments or tiers, such as “Hot,” “Warm,” and “Cold,” or Marketing Qualified or Sales Qualified, allowing sales teams to prioritize their efforts accordingly. Lead scoring facilitates more effective collaboration between marketing and sales teams, leading to improved conversion rates and overall revenue generation. The significance of lead scoring cannot be overstated. According to Marketing Sherpa, 61% of B2B marketers send any lead directly to sales without a lead qualification strategy, while sales reps ignore 70% of all leads from marketing, leading to significant inefficiencies and considered a top-three time-waster for sales teams. To address this issue and achieve sales and marketing alignment, businesses can take several steps, including defining their Ideal Customer Profile (ICP or Persona), tailoring communication and content to attract the right leads, collecting necessary data to qualify leads effectively, and identifying which leads match their profile and are ready to be handed over to the sales team. Analyze the steps in your customer jouneys by ICP or Persona and assign a score to the possible disposition of each step. While a bit stressful this is a great exercise in measuring historical data to see what really moves the needle in your sales cycles. While some steps are within a company’s control, others require technological support. One key tool for this is lead activity tracking, which collects data on lead engagement. Additionally, a lead scoring mechanism is needed to quantify lead interest and fit objectively. Unfortunately, Salesforce Marketing Cloud doesn’t offer satisfactory native functionality for activity tracking and lead scoring. However, there are several options to successfully track lead scoring within Salesforce, such as SalesWings, Marketing Cloud Connect and Process Automation, Marketing Cloud Journey Builder, and Marketing Cloud Personalization Builder and Predictive Intelligence, among others. Each option offers unique features and advantages, enabling businesses to tailor their lead scoring strategies to their specific needs and objectives. While Salesforce Marketing Cloud may lack native lead scoring capabilities, there are powerful ways to drive sales and marketing interactions effectively. The key is to base decisions on core marketing automation features and keep the goal of lead scoring in mind to align sales and marketing teams and personalize the customer experience based on intent. When a visitor goes to your website with the tracking code installed, a cookie is dropped with a unique ID and session ID. The cookie adds an ID to all Collect calls. The cookie tracks the user until it’s removed or cleared. The Collect Tracking Code pixel identifies itself as an invisible image, and it doesn’t affect the user experience of website visitors who use a screen reader. Configurations vary by product and use case. Collect Tracking Code monitors the variables and events that you select at the contact level. Considerations Salesforce Marketing Cloud may lack native lead scoring capabilities, there are powerful ways to drive sales and marketing interactions effectively. Base your decision on core marketing automation features and keep the goal of lead scoring in mind to align your sales and marketing teams and personalize the customer experience based on intent. All solution product descriptions are provided by their respective owners. Content updated May 2024. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

July 22, 2022in Google Analytics, Marketing Automation, Salesforce Marketing Cloud

Predictive Lead Scoring