Sellforte pricing
Performance
€2 490/moPerfect for eCom/D2C digital marketing teams in multi-market environment
- Onboarding support
- Data connectors for digital media
- Data connection to BI tool, data lake, data platform
- MMM Dashboard
- Campaign dashboard
- Media Optimizer
- Discounts and Promotions included as modeling variable
- New vs Returning customer split
- Multi-market results (Max. 10 markets + others)
- Daily model updates
- Customer success manager
Helping companies like
Modeling
- Number of business areas, products or brandsHave results split into different brands (ROI for BRAND x, ROI for brand Y, etc)1110
- Additional external variablesTrend, Seasonality, Holidays, Covid19 stringency index included as default. Additional external variables priced separately, e.g., Weather, Market indices, Competitor activities004
Brand
€3 490/moPerfect for local eCom/D2C marketing teams that use digital & offline media
Everything in Performance and
- Offline media
- Local digital media
- Update frequency: Daily for digital, monthly for offline media
Helping companies like
Modeling
- Number of business areas, products or brandsHave results split into different brands (ROI for BRAND x, ROI for brand Y, etc)1110
- Additional external variablesTrend, Seasonality, Holidays, Covid19 stringency index included as default. Additional external variables priced separately, e.g., Weather, Market indices, Competitor activities004
Enterprise
CustomFully customizable solution for omnichannel retailers with complex business needs
Everything in Brand and
- Modeling of offline sales data
- Customized amount of timeseries (e.g. 15 product categories and 2 sales channels)
- Custom media taxonomy
- Additional external variables
- Long-term sales modeling (Optional)
- Dedicated Customer Success Manager (Optional)
Helping companies like
| Detailed comparison | Performance | Brand | Enterprise | |
|---|---|---|---|---|
| Book a demo | Book a demo | Book a demo | ||
| Target KPI | eCom revenue or orders | eCom revenue or orders | Offline + eCom sales | |
| Long-term sales modelling Modeling long term sales, +28 days from the investment | - | - | ||
| Supermetrics applicability Option to use Supermetrics data connector for digital data imports | ||||
| Fivetran applicability Option to use Fivetran data connector for digital data imports | ||||
| Funnel.io applicability Option to use Funnel.io data connector for digital data imports | Additional Service | Additional Service | Additional Service | |
| Powered by Fivetran Option to use integrated data connector (Powered by Fivetran) for digital data imports without additional cost | ||||
| Custom business data connector Pulling Target KPI data from e.g. via Google Big Query, Snowflake, Amazon S3, etc. | ||||
| Offline media data imports with standard data template | - | |||
| Offline media data imports using custom data template | - | - | ||
| Data history | Up to 2 years | Up to 2 years | Unlimited | |
| Shopify | ||||
| BigCommerce | ||||
| Magento | ||||
| OsCommerce | ||||
| Salesforce Commerce Cloud | ||||
| Squarespace | ||||
| WooCommerce | ||||
| Google Analytics 4 | ||||
| Google Analytics | ||||
| Adobe Analytics | ||||
| Google Search Console | ||||
| Google Ads | ||||
| Microsoft Advertising (Bing) | ||||
| Facebook Ads | ||||
| TikTok Ads | ||||
| Snapchat Marketing | ||||
| Pinterest Ads | ||||
| Twitter Ads | ||||
| LinkedIn Ads | ||||
| Google Campaign Manager 360 | ||||
| Google Search Ads 360 | ||||
| Google Display & Video 360 | ||||
| Klaviyo | ||||
| MailChimp | ||||
| Criteo | ||||
| Adform | ||||
| Adtraction | ||||
| RTB House | ||||
| Amazon Ads | ||||
| Direct buys Local digital media bought directly that doesn't have a data connector | - | |||
| TV | - | |||
| Radio | - | |||
| OOH (Out-Of-Home) | - | |||
| Direct mail Offline and online direct mail or leaflets | - | |||
| - | ||||
| Magazine | - | |||
| Cinema | - | |||
| Standard external variables Trend, seasonality, holidays | ||||
| Granted discounts and promotions Modelling discount/promotion uplifts (if this data is available) | ||||
| Custom external variables Custom external variables, e.g., store network, distribution footprint, competitor media investments, weather | Additional Service | Additional Service | Additional Service | |
| Media driven sales / ROI See the impact that your marketing has had on business.
On ROI figures but also in sales | ||||
| Ad platform ROI Compare ROI between Google Ads, Facebook Ads, Microsoft Advertising, Snapchat Marketing, TikTok Ads, …and if you have offline channels TV, Radio, OOH, Print, Direct Mail, etc. | ||||
| Advertising channel ROI For performance marketing: Google Performance Max, Google Search Generic, Google Search Brand, Facebook Prospecting, Facebook Retargeting, Discovery, Display, etc.
If scope includes offline mediums, results on following level: TV3, TV4, Clear Channel, JcDecaux, Radio2, Radio3, Magazine5, Magazine6 etc | ||||
| Campaign ROI Get ROI for every campaign: Klaviyo_Welcome_series, Google_PMax_BrandX, Google_Search_BrandX, Google_Search_Discovery, Google_Search_Generic. Facebook_Video_Prospecting, Facebook_Video_Retargeting etc. | ||||
| Campaign objective ROI Split the results of each Ad platform campaigns to different campaign objectives like: Awareness, Traffic, Engagement, Leads and Sales | ||||
| Bidding strategy type ROI Compare ROIs between Target ROAS, Maximize Conversions, CPC, … | ||||
| Country specific ROIs Compare media ROI between different markets: Germany, The U.K., the U.S.A., Canada, Australia, New Zealand, France, Sweden, Finland, etc. | Additional Service | |||
| Customer type uplifts See how the campaign has lifted sales of New vs Returning customers | ||||
| Sales channel uplifts See how the campaign or medium has lifted sales in each sales channel. | - | - | - | |
| Product category uplifts Modeling built on a product category level. Enabling campaign / medium-specific uplifts per product category and cross-category effects i.e. from jacket campaign to hat category uplifts. | - | Additional Service | ||
| Campaign type ROI Compare campaign type performance between Brand campaigns, Tactical campaigns, Season-End campaigns | - | - | ||
| Customer segment uplifts B2C, B2B, Women, Men, Kids, … or Loyalty card holders and Non-Loyalty card holders | - | - | ||
| ROIs per brand Main Brand, Luxury Brand, Price Conscious Brand, Niche Brand, … | Additional Service | Additional Service | ||
| Custom media taxonomy During onboarding built custom media taxonomy for example for all media data to have campaign types data (Brand, Tactical, Always-On, Seasonal, etc) | - | - | ||
| Calibration with experiments and lift tests | ||||
| Optimal media investment level Use the scenario planning tool to find optimal media investment level for next year, quarter or month | ||||
| Optimal media group split Find out the optimal media split for each campaign type | ||||
| Optimal media split per market Optimize media investments across the markets to get the most out of your global media budget | ||||
| Optimal campaign type split Find optimal media split between brand, tactical, seasonal and always-on campaigns | - | - | ||
| Optimal media split across brand portfolio Optimize media investment between luxury brand, main brand, niche brand and low-price point brand | Additional Service | Additional Service | ||
| Digital media Digital media allows for higher update frequency (daily) | Up to daily | Up to daily | Up to daily | |
| Offline media Offline media modelling frequency | Monthly/Quarterly | Monthly/Quarterly | Monthly/Quarterly | |
| Standard data harmonization across channels | ||||
| Custom classifications Create custom classes of data, e.g., define that campaign objective can have values "Brand" or "Performance" | - | - | ||
| Custom rules Create custom rules for classifying data, e.g., define which strings within campaign names indicate that the campaign has "Brand" campaign objective | - | - | ||
| Custom transformations Rename campaign names, trim campaign names | - | - | ||
| Export as .xlsx Excel-file | ||||
| Export to data warehouse | - | - | - | |
| Number of users | 3 | 5 | 5 | |
| IP whitelisting | ||||
| VPN access | ||||
| Azure AD SSO | - | - | ||
| Google SSO | - | - | ||
| Email support | ||||
| Access to Sellforte Support Center | ||||
| Teams/Zoom support | ||||
| Dedicated Customer Success Manager | Additional Service | Additional Service | ||
| Quarterly Business Reviews (QBRs) | Additional Service | Additional Service | ||
| Standard Sellforte Terms of Service | ||||
Frequently asked questions
Digital
We use data connectors like Supermetrics and Funnel to automate all data pulls and updates. If you don't have a data connector already, Sellforte's sales will update you about a joint deal.
Growth
Digital media with data connectors and offline media with standard data templates or with custom data sources (extra costs)
Enterprise
Enterprise setup is always tailored for the customer, but we try to automate all the data updates as much as possible.
Again, Digital media is connected with connectors and offline media by using either templates or providing a data dump on Sellforte's Upload service during onboarding. Later those data sources will be automated
We would love to be as open as possible with the pricing, but sometimes it's not that easy to bring complex pricing to a simple website.
To be able to give out a price for an Enterprise solution we need to understand and consult about the modeling scope that is planned to be set up.
Also, the data quality, connections, automation level, used media groups, media data sources, modeled timeseries and service level plays a role in Enterprise pricing, so we figured out it's actually easier to discuss this over a video call and get a proposal afterwards.
This lets multiple different types of customers enjoy the product at a price level that takes into account their unique situation and the value they get from the product.
This pricing method was chosen at Sellforte since, in our opinion, customers view MMM SaaS solutions more in terms of the value the platform can give to their business than wanting to pay for the modeling work itself.
Since we know the value of MMM lies in media investments, it’s the most natural way the base the pricing on it. Whether your annual media budget is 300 000 € or 100 million € the impact is percentage-wise pretty much the same if there is only some complexity to be optimized.
Yes, this is a very typical way of implementing Sellforte since Digital is fast to implement and you start learning from the data faster.
On the other hand, if you use a lot of offline media, your results will change a bit after offline media is updated to the scope.
You also miss the opportunity to optimize the full entity immediately and make the most out of your budget.