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Two powerful tools, together

Integrate Salesforce and Workday RaaS to turn your data into actionable insights.

  • Salesforce

Salesforce is the #1 CRM platform

Stitch offers detailed documentation on how to sync your Salesforce data.

Stitch Salesforce Documentation

  • Workday RaaS

Workday RaaS offers enterprise-level software solutions for financial management, human resources, and planning

Stitch offers detailed documentation on how to sync your Workday RaaS data.

Stitch Workday RaaS Documentation

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Jumpstart your Salesforce analytics with reusable blocks

dbt packages can speed up your work

Once you replicate your Salesforce data with Stitch, you can use it in many ways. For example, you can use the data modeling and transformation tool dbt to prepare data for reporting, analytics, or machine learning applications.

Dbt has prebuilt packages for many Stitch data sources, including Salesforce. Here’s a look at code for modeling Salesforce data. This particular block of code creates a daily model of your Salesforce opportunities.

View the source on GitHub →
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 --the output of this model is a day per opportunity history that the opp was active {{ config( materialized='table', sort='date_day', dist='opportunity_id' ) }} {%- set custom_fields = var('opportunity_history_custom_fields') -%} with opp_history as ( select distinct date_trunc('day', created_date)::date as start_date, date_trunc('day', active_to)::date as end_date, opportunity_id, account_id, owner_name, stage_name {{ "," if (custom_fields|length) > 0 }} {% for custom_field in custom_fields %} last_value({{custom_field}}) ignore nulls over (partition by opportunity_id, created_date order by created_date rows between unbounded preceding and unbounded following) as {{custom_field}}{{"," if not loop.last}} {% endfor %} from {{ref('sf_opportunity_history_joined')}} ), days as ( {{ dbt_utils.date_spine(datepart="day", start_date="to_date('{{ var('first_record') }}', 'mm/dd/yyyy')", end_date="dateadd(week, 1, current_date)") }} ), opp_days as ( --this creates the final output of one row per day the stage was active select days.date_day, date_trunc('month', days.date_day)::date as date_month, opp_history.* from days inner join opp_history on days.date_day >= opp_history.start_date and days.date_day < opp_history.end_date ) select {{ dbt_utils.surrogate_key('date_day','opportunity_id') }} as id, * from opp_days

... or use Looker blocks with your Salesforce data

We've developed a Looker Block for Salesforce data provisioned by Stitch. This block includes prebuilt code to create dashboards and models that can help uncover insights from your Salesforce data.

This Looker Block includes three dashboards that provide analysis on sales and marketing leadership, sales ops management, and sales representative performance. The dashboards highlight top-level sales metrics, conversion rates between funnel stages, and various metrics to assess your pipeline health. The LookML file shown here produces a dashboard that can be used to monitor lost and won deals, revenue, and win rate by representative to evaluate performance of your sales organization.

View the source on GitHub →
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 - dashboard: representative_performance title: "Sales Representative Performance Dashboard" layout: grid rows: - elements: [count_won_deals, salesrep_total_revenue, count_lost_deals, win_percentage ] height: 150 - elements: [opportunities_to_wins_trend_peers] height: 400 - elements: [salesrep_revenue_won_comparison] height: 400 - elements: [salesrep_win_rate_comparison, salesrep_revenue_pipeline_comparison] height: 400 filters: - name: sales_rep type: field_filter explore: opportunity field: opportunity_owner.name - name: sales_segment type: field_filter explore: account field: account.business_segment elements: - name: count_won_deals title: 'Count of Won Deals (This Quarter)' type: single_value model: salesforce explore: opportunity measures: [opportunity.count_won] listen: sales_segment: account.business_segment sales_rep: opportunity_owner.name filters: opportunity.close_date: last quarter limit: 500 font_size: small text_color: '#49719a' width: 3 height: 2 - name: salesrep_total_revenue title: 'Salesrep - Total Revenue (This Quarter)' type: single_value model: salesforce explore: opportunity measures: [opportunity.total_revenue] listen: sales_segment: account.business_segment sales_rep: opportunity_owner.name filters: opportunity.close_date: 'last quarter' limit: 500 font_size: small text_color: '#49719a' width: 3 height: 2 - name: count_lost_deals title: 'Count of Lost Deals (This Quarter)' type: single_value model: salesforce explore: opportunity measures: [opportunity.count_lost] listen: sales_segment: account.business_segment sales_rep: opportunity_owner.name filters: opportunity.close_date: 'last quarter' limit: 500 font_size: small text_color: '#49719a' width: 3 height: 2 - name: win_percentage title: 'Win Percentage of Closed Deals (This Quarter)' type: single_value model: salesforce explore: opportunity measures: [opportunity.win_percentage] listen: sales_segment: account.business_segment sales_rep: opportunity_owner.name filters: opportunity.close_date: 'last quarter' limit: 500 font_size: small text_color: '#49719a' width: 3 height: 2 - name: opportunities_to_wins_trend_peers title: 'Opportunities to Wins by Rep' type: looker_line model: salesforce explore: opportunity dimensions: [opportunity.created_month, opportunity_owner.rep_comparitor] pivots: [opportunity_owner.rep_comparitor] measures: [opportunity.count, opportunity.count_won] dynamic_fields: - table_calculation: opportunities_to_won label: opportunities_to_won expression: 1.0*${opportunity.count_won}/${opportunity.count} value_format: '#.0%' hidden_fields: [opportunity.count_won, opportunity.count] listen: sales_rep: opportunity_owner.name_select filters: opportunity.created_month: 9 months ago for 9 months sorts: [opportunity.created_month desc, opportunity_owner.rep_comparitor] limit: 500 column_limit: 50 query_timezone: America/Los_Angeles stacking: '' colors: ['#FFCC00', '#1E2023', '#3399CC', '#CC3399', '#66CC66', '#999999', '#FF4E00', '#A2ECBA', '#9932CC', '#0000CD'] show_value_labels: false label_density: 25 font_size: small legend_position: center x_axis_gridlines: false y_axis_gridlines: true show_view_names: true y_axis_combined: true show_y_axis_labels: true show_y_axis_ticks: true y_axis_tick_density: default y_axis_value_format: '#%' show_x_axis_label: true show_x_axis_ticks: true x_axis_scale: auto show_null_points: true point_style: none interpolation: linear width: 12 height: 4 - name: salesrep_revenue_won_comparison title: 'SalesRep - Revenue Won comparison' type: looker_bar model: salesforce explore: opportunity dimensions: [opportunity_owner.rep_comparitor] measures: [opportunity.average_revenue_won] listen: sales_rep: opportunity_owner.name_select sorts: [opportunity_owner.rep_comparitor] limit: 500 query_timezone: America/Los_Angeles stacking: '' colors: ['#FFCC00', '#1E2023', '#3399CC', '#CC3399', '#66CC66', '#999999', '#FF4E00', '#A2ECBA', '#9932CC', '#0000CD'] show_value_labels: true label_density: 25 label_color: ['#3399CC'] font_size: small legend_position: center hide_legend: false x_axis_gridlines: false y_axis_gridlines: true show_view_names: false y_axis_combined: true show_y_axis_labels: true show_y_axis_ticks: true y_axis_labels: [Total Revenue Won] y_axis_tick_density: default show_x_axis_label: false show_x_axis_ticks: true x_axis_scale: auto show_null_labels: false width: 6 height: 3 - name: salesrep_win_rate_comparison title: 'SalesRep - Win Rate Comparison' type: looker_bar model: salesforce explore: opportunity dimensions: [opportunity_owner.rep_comparitor] measures: [opportunity.win_percentage] listen: sales_rep: opportunity_owner.name_select sorts: [opportunity_owner.rep_comparitor] limit: 500 query_timezone: America/Los_Angeles stacking: '' colors: ['#FFCC00', '#1E2023', '#3399CC', '#CC3399', '#66CC66', '#999999', '#FF4E00', '#A2ECBA', '#9932CC', '#0000CD'] show_value_labels: true label_density: 25 label_color: ['#3399CC'] font_size: small legend_position: center hide_legend: false x_axis_gridlines: false y_axis_gridlines: true show_view_names: false y_axis_combined: true show_y_axis_labels: true show_y_axis_ticks: true y_axis_labels: [Opportunity Win Rate] y_axis_tick_density: default show_x_axis_label: false show_x_axis_ticks: true x_axis_scale: auto show_null_labels: false width: 6 height: 3 - name: salesrep_revenue_pipeline_comparison title: 'SalesRep - Revenue Pipeline comparison' type: looker_bar model: salesforce explore: opportunity dimensions: [opportunity_owner.rep_comparitor] measures: [opportunity_owner.average_revenue_pipeline] listen: sales_rep: opportunity_owner.name_select sorts: [opportunity_owner.rep_comparitor] limit: 500 query_timezone: America/Los_Angeles stacking: '' colors: ['#FFCC00', '#1E2023', '#3399CC', '#CC3399', '#66CC66', '#999999', '#FF4E00', '#A2ECBA', '#9932CC', '#0000CD'] show_value_labels: true label_density: 25 label_color: ['#3399CC'] font_size: small legend_position: center hide_legend: false x_axis_gridlines: false y_axis_gridlines: true show_view_names: false y_axis_combined: true show_y_axis_labels: true show_y_axis_ticks: true y_axis_labels: [Total Revenue Pipeline] y_axis_tick_density: default show_x_axis_label: false show_x_axis_ticks: true x_axis_scale: auto show_null_labels: false width: 6 height: 3

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Give your analysts, data scientists, and other team members the freedom to use the analytics tools of their choice.

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Thanks to Stitch we get the granular insight we need into our data. Having our Salesforce and internal data in one place was a key factor in helping us scale out our new business function.

Taylor Udell

Lead Solutions Architect, Heap

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Why our customers choose Stitch

Stitch is a simple, powerful ETL service built for developers. Stitch connects to your first-party data sources – from databases like MongoDB and MySQL, to SaaS tools like Salesforce and Zendesk – and replicates that data to your warehouse. With Stitch, developers can provision data for their internal users in minutes, not weeks.

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