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Sales Analytics Jobs in California (NOW HIRING)

We are seeking a data-driven Manager, Sales Analytics to lead day-to-day sales, traffic, and average check analysis and to build and maintain the forecasting models that inform planning, marketing ...

MANAGER, SALES ANALYTICS

Costa Mesa, CA ยท On-site

$90 - $130/hr

We are seeking a data-driven Manager, Sales Analytics to lead day-to-day sales, traffic, and average check analysis and to build and maintain the forecasting models that inform planning, marketing ...

MANAGER, SALES ANALYTICS

Costa Mesa, CA ยท On-site

$113K - $127K/yr

We are seeking a data-driven Manager, Sales Analytics to lead day-to-day sales, traffic, and average check analysis and to build and maintain the forecasting models that inform planning, marketing ...

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Sales Analytics information

See California salary details

$82.9K

$106.6K

$178.1K

How much do sales analytics jobs pay per year?

As of Aug 29, 2026, the average yearly pay for sales analytics in California is $106,585.00, according to ZipRecruiter salary data. Most workers in this role earn between $88,300.00 and $98,200.00 per year, depending on experience, location, and employer.

What is sales analytics?

Sales analytics is the process of collecting, analyzing, and interpreting data related to sales performance, customer behavior, and market trends. Professionals in sales analytics use various tools and techniques to identify patterns, forecast sales, and provide actionable insights to help businesses make informed decisions. This role typically involves working with large datasets, creating reports and dashboards, and collaborating with sales teams to optimize strategies and achieve revenue goals.

What are the key skills and qualifications needed to thrive as a sales analytics professional?

To thrive as a Sales Analytics professional, you need strong analytical skills, a background in statistics or business, and experience with data interpretation, typically supported by a relevant degree. Proficiency with tools such as Microsoft Excel, SQL, Salesforce, and data visualization platforms like Tableau or Power BI is essential. Attention to detail, critical thinking, and effective communication are standout soft skills for translating complex data into actionable insights. These skills and qualities are crucial for driving data-informed sales strategies and supporting business growth.

How does a sales analytics professional typically collaborate with sales and marketing teams to drive business decisions?

Sales Analytics professionals work closely with both sales and marketing teams to translate data insights into actionable strategies. They often collaborate in regular meetings to review sales performance metrics, identify trends, and pinpoint areas for improvement. By providing data-driven recommendations, they help teams optimize campaigns, refine targeting, and allocate resources more effectively. This role often acts as a bridge, ensuring that analytical findings are clearly communicated and implemented to achieve business goals.

What is the difference between Sales Analytics vs Sales Operations?

AspectSales AnalyticsSales Operations
Primary FocusAnalyzing sales data to identify trends and insightsManaging sales processes and supporting sales teams
Required SkillsData analysis, reporting, visualization, CRM proficiencyProcess management, CRM tools, sales strategy
Work EnvironmentData-driven, analytical, often in a corporate settingOperational, cross-functional, supporting sales teams
Common CertificationsSalesforce certifications, data analysis certificationsCRM certifications, sales management courses

Sales Analytics focuses on interpreting sales data to inform strategic decisions, while Sales Operations manages the sales process and supports sales teams to improve efficiency. Both roles require familiarity with CRM tools and data skills, but their core responsibilities differ significantly.

Is sales analytics a high paying job?

Sales analytics is generally considered a well-paying role within data and business analysis fields, with salaries often higher than average for entry-level positions. Compensation varies based on experience, location, and industry, and professionals with skills in data visualization tools and statistical analysis tend to earn higher salaries.

What are the most commonly searched types of Sales Analytics jobs in California?

The most popular types of Sales Analytics jobs in California are:

What are popular job titles related to Sales Analytics jobs in California?

For Sales Analytics jobs in California, the most frequently searched job titles are:

What job categories do people searching Sales Analytics jobs in California look for?

The top searched job categories for Sales Analytics jobs in California are:

What cities in California are hiring for Sales Analytics jobs?

Cities in California with the most Sales Analytics job openings:

Infographic showing various Sales Analytics job openings in California as of August 2026, with employment types broken down into 84% Full Time, 15% Part Time, and 1% Contract. Highlights an 78% Physical, 1% Hybrid, and 21% Remote job distribution, with an average salary of $106,585 per year, or $51.2 per hour.

MANAGER, SALES ANALYTICS

Costa Mesa, CA โ€ข On-site

loco
1 - 10 employees

Full-time

Posted 16 days ago


Job description

POSITION PURPOSE:

We are seeking a data-driven Manager, Sales Analytics to lead day-to-day sales, traffic, and average check analysis and to build and maintain the forecasting models that inform planning, marketing, and pricing decisions across the business. This role partners closely with the Senior Manager, Marketing Analysis to evaluate marketing, promotional, menu, and channel performance, and translates performance data into clear, actionable recommendations for Marketing, Finance, and Operations. This role uses EPL's governed data environment and established business rules to produce analysis โ€” it is not responsible for data architecture, ingestion, or governance, which are owned by IT.

ESSENTIAL DUTIES AND RESPONSIBILITIES:

ย 

  • ย Own recurring and ad hoc analysis of comp sales, comp traffic, and average check across Company, Franchise, DMA, etc. levels, applying EPL's established data definitions and comp methodology consistently.
  • Build, maintain, and continuously refine sales and traffic forecasting models โ€” incorporating historical performance, seasonality, promotional calendar, media, pricing, digital channels, loyalty and market conditions โ€” to support weekly, period, and quarterly reporting & planning cycles.
  • Support annual and quarterly planning through scenario modeling and variance analysis, in partnership with the Senior Manager, Marketing Analysis.
  • Evaluate marketing, pricing/discount, menu, and promotional performance (including LTOs, etc.), and maintain breakeven models to assess the volume/margin trade-offs of pricing and promotional decisions, to identify growth opportunities and inform go-to-market recommendations.
  • Analyze product mix and guest segmentation using internal and third-party data sources to uncover channel and campaign optimization opportunities.
  • Own analysis and forecasting of sales, traffic, and check trends by channel (Drive Thru, Off-Premise Pickup, Dine-In, Delivery/3PD, Digital/Mobile, etc.) to identify share-shift patterns and growth or erosion by channel across Company and Franchise.
  • Analyze the impact of channel mix shift on average check and margin, including how migration toward delivery, marketplace, and digital ordering affects discounting, commission drag, and basket size relative to Drive Thru and Dine-In.
  • Evaluate digital ordering (app/web) and loyalty engagement trends as leading indicators of guest frequency, connecting digital behavioral data to sales and traffic outcomes.
  • Assess third-party delivery marketplace performance (order volume, average order value, growth rate by partner, etc.) to inform promotional and commission-strategy trade-off discussions with Marketing and Finance.
  • Incorporate channel-specific seasonality and digital/off-premise growth trajectories into forecasting models rather than treating digital and delivery channels as a flat add-on to in-store trends.
  • Partner with Consumer Insights to incorporate industry trends, competitive dynamics, and consumer behavior into performance narratives.
  • Build and maintain executive-ready dashboards and reporting with intent-based channel groupings, YoY comparisons, and Company/Franchise/DMA views, using data and business rules maintained by IT.
  • Support test-and-learn initiatives โ€” including A/B tests, controlled pilots, etc. โ€” by designing analysis plans and reading out results for marketing, pricing, and menu strategies.
  • Flag data anomalies or inconsistencies encountered during analysis through EPL's established data governance process, routing issues to IT rather than resolving them directly.
  • Synthesize complex data into clear, compelling narratives and present findings and recommendations to Marketing and cross-functional leadership.
  • Perform ad hoc analysis and other duties as assigned to support evolving business needs and priorities.

QUALIFICATIONS โ€“ EDUCATION, EXPERIENCE, LICENSE/CERTIFICATIONS:

To perform this job successfully, an individual must be able to satisfactorily perform the essential functions of the job.ย  Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions of the job.ย  The requirements listed below are representative of the education and/or experience required.ย 

ย 

Education/Work Experience:

  • Bachelor's degree in Business, Finance, Marketing, Economics, Statistics, or related field.
  • Advanced degree (MBA or Master's in Analytics) a plus.
  • 4โ€“6 years in sales, marketing, or business analytics, with demonstrated forecasting experience; QSR, restaurant, or other multi-unit consumer-facing industry preferred.
  • Experience analyzing digital ordering, loyalty, delivery marketplace, or other off-premise/e-commerce channel performance strongly preferred.

Knowledge, Skills, and Abilities:

  • Proven ability to build and maintain sales/traffic forecasting models and translate them into planning inputs.
  • Strong working knowledge of SQL for querying (not architecting) a cloud data warehouse environment.
  • Advanced proficiency in Excel/Sheets and data visualization tools (Power BI, Tableau, Looker, etc.).
  • Comfort using AI-assisted tools to improve analytical speed and productivity, paired with sound judgment to verify accuracy before outputs are used in decision-making.
  • Demonstrated strength in executive storytelling: able to translate data into clear, compelling recommendations.
  • Strong problem-solving skills, intellectual curiosity, and comfort working within a data environment that is actively being cleaned up and governed by IT.
  • Strong relationship builder with the ability to influence at all levels of the organization.
  • Ability to work at the Support Center consistent with the hybrid work policy.
  • Ability to work collaboratively in a fast-paced, dynamic environment.