Deliver Data-Driven Outcomes


Increased market pressure from domestic and international competition is causing online and physical commerce to converge. Simultaneously, companies are grappling with the challenge of maintaining profits while engaging clients.

It is necessary for companies to look at optimizing both bottom line and top line. As such, Big Data and advance analytics move us away from making decisions using gut feeling to a data-driven process supported by Artificial Intelligence, Machine Learning, robotic process automation, and real-time analytics.   SafeRock has deep experience in building powerful systems that improve business decisions. Our proprietary algorithms and data science techniques help us to power our ‘Best-in-Class’ ROI analytics. These systems are proven to reduce working capital, improve demand and sales forecast accuracy, increase online and store traffic, and reduce out-of-stock. 

BIG DATA AND ADVANCED ANALYTICS: CASE STUDIES

We can help transform your marketing from a cost center to a profit center with tools such as our ‘best in class’ promotion optimization system.

How does our system help to do this? SafeRock focuses on helping you optimize the allocation of your scarce marketing dollars to increase profits and/or sales. We analyze every promotion for incremental sales and incremental profits over baseline. By doing this we improve the efficacy of your overall campaign, and we also increase store and online traffic, as well as total sales and gross profits.

  • Increasing Marketing Profits

    Increasing Marketing Profits and Optimizing Omnichannel Sales    Situation
    • A $5+ billion dollar North American retailer wanted to optimize promotions and build a system to continuously improve merchandising and marketing ROI.
    • The goal was to improve investment and budgeting decision. This is an international chain of department stores.
    Approach
    • Working with the CMO, CIO, and merchandising and marketing teams, we developed an ROI-based strategy to improve promotion effectiveness. Our joint team designed a cloud-based ‘Big Data’ solution to measure promo effectiveness with extreme accuracy. The system analyzed over 100 million records for 1+ million SKUs, using 500+ simultaneous seasonal models. Our system and algorithms were integrated with Oracle™ and Teradata™.
    Result
    • The solution delivers precise KPIs that ‘sheds light’ and allows accurate performance comparison across all merchandise categories. Due to its extreme accuracy, our system became the ‘system of record’ for the company. Users include senior management, (CXO, GMM and DMM) and all merchandising and marketing managers. 
  • Creating Profit Centers

    Creating Profit Centers: Optimize the ROI for each and every Market   Situation
    • A $6 billion regional chain of 400+ supermarkets was facing stiff competition due to competitor store openings and internal inability to improve the performance of weekly ads and promotions. This led to weakened market share.
    Approach
    • We worked with both IT and merchandising to gather item, ad, and category sales and link these to space allocation. We then established a system to crunch ’near real-time’ sales data across all promotion items at the store level, and systematically combined this with data on item pricing, ad space, and category space allocation.
    Result
    • The system correctly Identifies all category winners and losers.
    • Ranks weekly sales from top to bottom in terms of ad performance.
    • Effectively prioritizes ad space allocation for merchandise categories.
    • Successfully improves promotion and offer allocations.
  • Competitive Improvement

    Improving Competitiveness by Bridging Merchant and Marketing Silos      Situation
    • This $12 billion, 800+ store national retailer wanted an enterprise system to bridge departmental ‘silos’ and bring Marketing and Merchandising closer together. This would enable Management to make better decisions on budgets, inventory, and marketing, which would in turn improve P&L, and effectively optimize the allocation of vendor funds.
    Approach
    • We designed and implemented an Oracle RDBMS-based central store of data for sharing of information across Marketing, Merchandising, and Finance departments.
    • We integrated item, copy, and price information to the online system.
    • We installed the solution and trained all users.
    Result
    • We successfully managed over 2 million store-level item price points.
    • We bridged the departmental ‘silos’ of Merchandising, Marketing, and Finance with a single workflow system.
    • We successfully decreased out-of-stocks on promotional items and established a Single System of Record for promotions and marketing events.

INCREASED ROI FOR OMNI-CHANNEL: CASE STUDIES

SafeRock’s proprietary tools and algorithms can improve the profitability of omni-channel marketing. And we can integrate our tools with your existing commerce solutions to support your exact needs.   In addition, our analytics and Data Science teams can work with you to improve your efficacy and eliminate bottlenecks at all customer touch points including mobile, store, and omni-channel.
  • Improving Customer Satisfaction

    Reducing Out-of-Stock and Improving Customer Satisfaction   Situation
    • The specific challenge for this $8 billion specialty retailer with 500+ stores was to improve buyer sales projections and reduce the recurrence of out-of-stock items. Frequent stock-outs of promotional items were turning customers off. This also had impact on supply chain and inventory costs.
    Approach
    • Our approach was to work with supply chain, IT, marketing, and merchants to gather item, ad, and category sales data and use this to evaluate performance. We then built a system for reporting performance at the item, category, and department level. We generated actual vs. forecast measures, ROI, and ad lift. We combined sales data for all promoted items with total sales and entire category sales, as well as item pricing, and promotion analysis.
    Result
    • Using a coherent strategic plan, we worked successfully across multiple company teams and tiers and then built a powerful system that generated highly accurate forecasts, improved buyer planning, and reduced excess inventory.
  • Improving the Customer Journey

    Improving the Customer Journey and Increasing Top line Sales   Situation
    • A regional supercenter chain in the Northeast US wanted a scientific, analysis-driven, system that would improve Merchandising’s item selections and promotion planning. They also wanted to simultaneously link marketing and co-op funds.
    Approach
    • Our approach was to work in a team across merchandising, advertising, and vendor fund management groups. We measured promotion ad lift by item, volume and profit. This created an analytics-based process for item selection and promotion.
    • The new process went from merchandise review and item selection, to FP&A improvement, and marketing efficiency.
    Result
    • Our solution successfully delivered analytics-driven ad item selection for the top 1,000 items weekly. It improves promotional fund tracking, and automates versioning of marketing messages across all customer touch points.
    • Quickly identified ‘cherry-pickers’ and capitalized on this to attract better shoppers and increase transaction basket size.
    • Recovered millions of dollars in ‘leaky’ vendor funds.
    • Increased omni-channel vendor fund usage to over $20 million. 
  • Enabling Digital Content

    Enabling Nimble Digital Content for Financial Literacy   Situation
    • A leading non-profit organization that provides economic and financial education to K-12 students wanted to create digital content, expand its e-learning platform, and increase engagement. The organization supports 50,000+ teachers across the United States who teach over 5 million students each year.
    Approach
    • We worked with the COO, the VP of Content, and IT resources to put together the digital transition.
    • Our team provided strategy, project management, digital content, e-learning goals as well as the technology that made this transition possible.
    Result
    • As a result of our work, the non-profit was able to successfully transition from print content to digital and mobile content while keeping to their timeline and budget.

OIL & GAS: CASE STUDIES

In the Energy sector, SafeRock has built a uniquely powerful predictive system for oil and gas fracking for basins in Eagle Ford, Permian, and Bakken. A case in point is our proprietary Big Data algorithms that forecasts production for oil and gas wells with great accuracy and automatically identifies anomalies and outliers at the well level.
  • Beat Top Energy Analysts

    System beats Top Energy Analysts in forecasting oil and gas production   Situation
    • A top-rated US energy analyst firm wanted to improve production forecast accuracy for public E&P operators in Lower 48. The challenge was to beat engineering experts using the same data for basins in Eagle Ford, Permian, and Bakken. 
    Approach
    • Using public data, we built a unique process using proprietary algorithms that takes well-level monthly oil and gas production data from E&P operators and builds unique models for each well.
    • The ARPS model was combined with SafeRock’s algorithms and compared against human engineer-estimated EUR for 1,200+ wells. The system proved so accurate it was subsequently expanded to forecast production for 100,000+ wells. 
    Result
    • The new system proved more accurate than experts more than 60% of the time.
    • This was dramatically faster by a factor of x100 for production forecasts for oil and gas and EUR.
  • Integrated Energy Solution

    Oil and Gas Type Curves auto-generated for Integrated Energy Producer   Situation
    • Energy companies need type curves to estimate area production, new well output and present production profiles to investors and shareholders.
    • Our goal was to generate dynamic type curves for any given set of wells.
    Approach
    • ARPS model was used as a basis for calculation.
    • We automatically calculated custom Type Curves for any given set of wells.
    • Significantly improved the accuracy and speed for creating type curves for 10 to 100,000 wells. 
    Result
    • We succeeded in building dynamic type curves that were more accurate than existing methods.
  • Major Energy Fund

    Fast System uses Big Data to model oil and gas well in Eagle Ford and Permian    Situation
    • The challenge was to generate output estimates better, faster, and cheaper than traditional methods.
    Approach
    • System took public data and APRS models, and ensured best fit to historical production.
    Result
    • Generated dynamic well models for up to 100,000 wells.
    • This process is better, faster, and cheaper and is ‘best in class’.

SAFEROCK SPOTS CARRIZO’S (NASDAQ: CRZO) STOCK SURPRISE 2 MONTHS IN ADVANCE

  • News Update

    News Update: February 28, 2018   On February 26, 2018, Carrizo’s (NASDAQ: CRZO) stock tumbled -23% and the company reduced the value of its Eagle Ford EUR assets by -14%. SafeRock had identified Carrizo’s production anomalies in December, two months earlier. 
  • Analyst Comment

    “SafeRock’s analysis of Carrizo was correct. Carrizo’s announcement (on 2/26/17) confirms that their EFS was underperforming meaningfully.” -Top Industry Analyst
  • Case Study

    TOROS predictive analytics correctly identified miss Analyst Report: 2/27/18 “Carrizo Oil and Gas 4Q17 quick look (CRZO $17.64 – M) – Really bad   Summary Thoughts – This is among the worst releases we have seen this earnings season and that’s saying something.  CRZO is guiding 2018 oil production ~8% below the Street, capex 10% above the Street… and a 10% cut to Eagle Ford oil EURs from 423 Mbo to 382 Mbo despite a 5% increase to lateral length.”
oil