Account Spark Guide for Admins

  • Technical Architecture

Account Spark is built 100% natively on the Salesforce ecosystem, leveraging multiple Salesforce clouds to produce a powerful and secure, insight-driven platform for our users. This means that your data never leaves the Salesforce Cloud, and along the way your data is handled within the highest guideles of Salesforce’s Trust policies.

The engagement layer is comprised of beautiful Lightning components that sit on top of your Sales cloud instance.  For classic users, no need to worry… our visual user interface will work for you too. There are many Lightning components including the Matrix page where you can see all of a user’s accounts plotted against two metrics, Potential and Probability. The Matrix page allows you to zoom into any of the four quadrants, multi-select accounts of interest, toggle to list view, and group action these accounts including logging a data quality ticket, exporting to a spreadsheet, and producing an email distribution in Salesforce Pardot. Another important Lightning component is the Account Summary page where you can see detailed insights about any particular account. You can see a product level breakdown of potential and probability, lookalike customers who may be able to help in reference selling to the target account, and an opportunity breakdown both historically over the last several years and forward looking over the next several quarters. This engagement layer acts to keep all of your users from sales reps to executives truly engaged with Account Spark.

Next there is the CRM infrastructure layer where we have a managed package of custom code that helps you get the most out of your Salesforce instance. We have created multiple new objects with hundreds of fields, custom report types, and Apex triggers to ensure that your insights are always fresh and up to date with the latest and greatest information. This CRM infrastructure layer is invisible to most users, except for system admins, so that users are not focused on the “so what” rather than the “how” of account scoring. Included in the layer is an integration to Salesforce’s Marketing Cloud, specifically Salesforce Pardot for mass email communications. Imagine you are a marketeer looking to invite prospective clients to a large event in an international top city. With Account Spark, you can instantly identify all accounts located within a 50-mile radius of this top city, hand select the ones with compelling potentials and probabilities, and then migrate your work to Pardot where you can produce an email distribution list filtered for those who have opted out. What used to take weeks now takes seconds thanks to the Account Spark CRM Infrastructure layer.

The final piece in the Account Spark technical architecture is the Data Science layer which touches Heroku and Einstein Platform Services. The Data Science layer is where all of our complex calculations happen including supervised machine learning on historical performance data. The client’s data (primarily what’s contained within the Account object, the Opportunity object, and the Task object) is transferred securely via Heroku Connect into a customer-unique Postgres database where we filter the data based off of the custom settings, discover trends, predict behavior, and push back actionable insights to the underlying CRM Infrastructure Layer.

In the end, our trifurcated architecture combines human judgement with machine learning to produce powerful predictions that are specific to your business. Setup is a breeze with no need for costly implementation partners. A lot of thought went into our architecture and we believe the end result is elegant and robust, allowing your business to grow sustainably over the coming years.

See the following illustration of our technical architecture:

  • Account Spark Data Architecture
    1. Account Summaries
    2. Product Summaries
    3. Cohort Analysis
  • Recursive Families
  • Top Cities methodology and the integration to ArcGIS

At a high level, users value the ability of identifying accounts that reside near a major metropolitan area. As an example, marketing specialists oftentimes create email distribution lists for major accounts (both customers and prospects) that are headquartered nearby an event location so that they may be invited to the event.

Our solution for Account Spark simplifies, solves, and scales this process in three easy steps. At first, we define top cities in a reasonable and consistent manner across the world. Metropolitan cities are defined as the grouping of all accounts that reside within a 50 mile radius of a predefined top city. This way, San Francisco Bay Area, for example, would be clearly defined as a geographical circle centered in the city center of San Francisco with a radius of 50 miles. Similarly, Mumbai would be consistently defined. Note that 50 miles was chosen as a reasonable drive time for customers and prospects as they look to attend an event. These predefined top cities were carefully chosen to avoid any overlap between two large cities that are in close proximity to each other (e.g. San Francisco, San Mateo, San Jose were combined into San Francisco Bay Area).

Next we must geocode each account address into latitude and longitude. Salesforce by default has native shipping and billing addresses that are comprised of a street, city, state, and country fields. Here Account Spark geocodes these addresses and transform them into a simple latitude and longitude. ArcGIS by ESRI has an API that can do this transformation and so the approach here has been to integrate this API into our application while upholding our security standards and exceeding the requirements of the Salesforce AppExchange.

Lastly, we added a “Top Cities” custom field and tagged each account with the name of the top city that is within a 50 mile radius. If there is a predefined top city within a 50 mile radius then the custom field value becomes the name of the Top City (e.g. San Francisco Bay Area). If there is no predefined top city within a 50 mile radius then the custom field value becomes “All Other Locations”.  And voila! That’s how any Account Spark user can easily identify which accounts are close to their upcoming event and invite contacts to attend.

The following list of top cities and their city centers are default in the Account Spark system. They were carefully chosen to cover the top metropolitans globally across a variety of metrics including population and Gross Domestic Product (GDP) while avoiding intersection.

Top City Region Latitude Longitude
Atlanta (US) AMER-US 33.7676338 -84.560689
Baltimore (US) 39.2848182 -76.690698
Boston (US) 42.3145182 -71.110711
Chicago (US) 41.8339032 -87.872391
Cleveland (US) 41.4977038 -81.846287
Dallas (US) 32.8208747 -96.871971
Denver (US) 39.7645183 -104.99554
Detroit (US) 42.3523699 -83.379389
Houston (US) 29.8174768 -95.682168
Los Angeles (US) 34.0207289 -118.69261
Miami (US) 25.7825452 -80.29967
Minneapolis (US) 44.9707969 -93.33169
New York (US) 40.6976684 -74.260553
Philadelphia (US) 40.0026763 -75.258461
Phoenix (US) 33.6056695 -112.40593
Pittsburgh (US)
40.4314779
-80.050712
Portland (US) 45.5428626 -122.79481
San Diego (US) 32.824816 -117.38985
San Francisco (US)
37.7578149 -122.50781
Seattle (US) 47.6131742 -122.48249
St. Louis (US) 38.6532846 -90.38389
Tampa (US) 27.9947144 -82.594709
Washington D.C. (US) 38.8937796 -77.155004
Montreal (CA) AMER-CA 45.5581964
-73.870729
Toronto (CA) 43.6570304 -79.601721
Vancouver (CA) 49.2578262 -123.19412
Birmingham (GB)
EMEA-UK 52.4775636 -2.0040575
London (GB) 51.5287714 -0.2420248
Manchester (GB) 53.4723271 -2.2936741
Dublin (IE) 53.3244427 -6.38613
Paris (FR) EMEA-FRANCE48.8589506
2.2768485
Berlin (DE) EMEA-DACH 52.5069296 13.1438663
Frankfurt (DE) 50.1213475 8.4961375
Munich (DE) 48.1550543 11.4014091
Vienna (AT) 48.2208282 16.2396334
Copenhagen (DK)
EMEA-NORDICS 55.6713441 12.5236127
Stockholm (SE) 59.3262416 17.8416275
Barcelona (ES) EMEA-IBERIA 41.3948975 2.0785562
Madrid (ES) 40.4381307 -3.8199642
Lisbon (PT) 38.7437395
-9.2304149
Milan (IT) EMEA-ITALY 45.4628327 9.1075207
Rome (IT) 41.9102411 12.3955705
Amsterdam (NL) EMEA-BENELUX 52.3547746 4.758197
Tel Aviv-Yafo (IL) EMEA-MIDDLE-EAST 32.0880576 34.7270341
Dubai (AE) 25.075706 54.9468685
Cairo (EG) 30.0595581 31.223359
Jeddah (SA) 21.4505278 38.9302698
Istanbul (TR)
EMEA-ROEMEA 41.0054989
28.7313076
Moscow (RU) EMEA-EMERGING 55.5815182 36.8237499
St. Petersburg (RU) 59.9396916 29.5289283
Cape Town (ZA) -33.913123 18.0942496
Johannesburg (ZA) -26.17135 27.9698128
Osaka (JP) JP-JP 34.6784656 135.460045
Tokyo (JP) 35.6735404 139.56996
Melbourne (AU) APAC-ANZ -37.970148 144.491335
Sydney (AU) -33.847355 150.651103
Bangalore (IN) APAC-INDIA 12.9542944 77.4905099
Hyderabad (IN) 17.4126272 78.2676161
Mumbai (IN)
19.0825221 72.7407568
New Delhi (IN) 28.5275195 77.0685563
Seoul (KR) APAC-KOREA 37.565289 126.849122
Jakarta (ID) APAC-ASEAN -5.7759349 106.116123
Manila (PH) 14.5965787 120.944454
Singapore (SG) 1.3143394 103.70382
Bangkok (TH) 13.725108 100.35223
Beijing (CN) APAC-GCR 40.2484481
115.345132
Guangzhou (CN)
23.1259806 112.946965
Hong Kong (CN) 22.352991 113.987271
Shanghai (CN) 31.2243025 120.914923
Taipei (TW) 25.0174716 121.365949
Rio de Janeiro (BR) LACA-BRAZIL -22.913251 -43.726858
São Paulo (BR) -23.68153 -46.876175
Mexico City (MX) LACA-MEXICO 19.3910036 -99.284042
Bogotá (CO) LACA-ROLACA-NOLA 4.6486259 -74.248237
Buenos Aires (AR) LACA-ROLACA-SOLA -34.615662 -58.50351
  • Integration to Pardot
  • Heroku Connect and the secure syncing process
  • Data Quality Cases
  • Setup Wizard
    1. Organizational Settings
    2. Mapping Settings
    3. Product Settings
    4. Data Science Settings
    5. API Triggers
  • Recommendations Engine
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Published: 05/03/2019

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