How to Make Channel Data Partnerships into Engines for Growth

This week, we’ve explored how you can use channel partnerships to develop your data products, make your brand recognizable, and leverage the skill sets of other companies to drive growth.  Affiliate partnerships give you the benefit of finding new customers and supplementing your areas of weaker (or at least less strong) competency.  Reseller partnerships broadcast your data to new markets in a less labor-intensive way, all while giving you a reputation as a good provider of content.  Between these two models, you are almost certain to find ways to take your existing data and turn it into a vehicle for growth.

Data partnerships, though, are all about flexibility, and so you may find that the neat division of the world into affiliates and resellers doesn’t really work for your company.  Not to worry — you may not need to decide.

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She got made an SVP for this.

Hybrid Models

The Best of Both Worlds

As we have discussed, the two models of affiliate or reseller channel data partnerships cover the majority of scenarios you will encounter as you bring your dataset to market. There are, however, some hybrid opportunities to consider. Hybrids attempt to mitigate some of the risks noted above by segmenting the opportunities or sales territories for each program.

For example, when you have a direct sales team and wish to employ a channel data partnership approach as well, sales conflicts are bound to occur where one team feels the other is blocking them or, worse, has stolen a commission or opportunity. To prevent this, create a hybrid model that separates commissions based upon the size of the customer being sold to. In this way, your company can have partners that sell to small businesses as a reseller, but may only sell to larger businesses as an affiliate. This has the additional benefit of ensuring that your partner handles smaller customers’ service while your team handles larger customers’ service. Given that you own the direct client relationship in affiliate transactions, the hybrid model aligns your internal team’s efforts with efforts to make the most of each introduction to the largest number of customers.

Because the direct sales team is often the most experienced and knowledgeable about the dataset they represent full-time, they should be focused on bringing in the largest deals. Resellers and affiliates, on the other hand, are better at representing several different solutions and may have a host of different datasets in their offering from different providers. Allowing your channel data partners to resell your data to smaller businesses is a great way to scale your business as you limit them only to sales that aren’t huge opportunities for your internal sales team. Marking a limit to the opportunity size, perhaps by factors like target company revenue, employee count, licenses needed, or any other reasonably appropriate metric that draws the line for a prospective customer size, will keep the reseller from battling your direct sales team and creating inter-team conflict.

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No one wants to see that.

If you employ this strategy, it will be a sensitive subject with your resellers. Reseller partners typically want to also sell to large businesses, and they don’t love the concept of being limited to just smaller client opportunities. This is why it is your responsibility to make the affiliate solution, where the partner receives compensation for large opportunity introductions, a compelling compromise. Whether financially through a large percentage revenue share, or through a type of exclusivity, or other favorable term, it is vital that you maintain a positive relationship where you reward introductions by channel data partners to help your team on both the low and high ends of the market.

Hybrid models deliver both the reseller scale and the affiliate control of the customer that data providers desire. The negotiation can be difficult to complete, but if all parties are honest about their actual capabilities, you can identify the right mixture of features together. Unfortunately, we have seen many partnerships fail at the goal line because of the less-than-humble attitude by one side or both as to their own team’s sales and service capabilities. As we’ve pointed out many times, partnerships have two keys to success: leadership and humility. In channel data partnerships, the latter is often very difficult to maintain during each negotiation, but nothing sours business partnerships quite like arrogance or an overhyped sense of self-importance.

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Not a good strategy (unless you’re actually Ali).


Once you’ve chosen whether a hybrid or a traditional model works, the task is only partially done.  It’s essential to cultivate, grow, and attend to how the partnership is helping your business grow, which means attention both to detail and to the end result with consumers.  One of the best ways to build out your channel data partnership strategy is to identify a segmentation strategy for your products and services. By segmenting your solution, you can keep resellers, affiliates, and direct sales teams from running head first into each other in the market. The benefits can protect both you and your channel data partnerships, but can make tracking complex. There are countless ways to segment a data offering, but most are combinations of four approaches.

Data or Product Segmentation

We have analyzed many strategies that segment a data offering. You can use depth, timeliness, or coverage to segment data. In each case, you offer a particular combination of datasets to each partner or group of partners focused on a particular client base. For example, you can segment your offering by providing the data over a historical timeframe versus a real-time delivery approach. Perhaps only affiliates could introduce the real-time solution, while resellers could show historical data after a certain time embargo. This is how many data providers segment stock charts and price data as well as other fundamental financial datasets.

You can successfully segment data by depth, with certain details or fields being reserved to only certain partnerships. For example, some business valuation data may only be available at a sector or market level through one partner, while the individual company valuation analysis is reserved for bigger partners with larger commitments to the product.


You can also use derivative datasets to create segmentation. When your channel data partner has their own unique data, an ideal strategy is to merge your data with theirs to create a derivative work, only available through them. Consider the Zillow Zestimate, which makes an estimation of any home price by merging, analyzing, and calculating values based on dozens of different data sources. If you were one of the data partners that provides data to Zillow, you can eliminate competition for other partners by limiting Zillow’s use of your data to their Zestimate calculation. In this way, your particular dataset may not be fully revealed, but only exist as a component of the Zestimate, thus ensuring this partnership doesn’t adversely affect other opportunities for your data products.

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“Say ‘Zestimate’ again, I dare you.”

Geographic Segmentation

Data knows no borders, and yet geography is still a very popular way to segment your data partnership strategy. We have seen many successful partnerships segmented by country or even continent. We do not recommend segmenting into any smaller geographic regions than at the country level.

To segment by country, start by identifying the market dynamics at work. Is the country more monopolistic in the way businesses operate or does it tend to be more fragmented and competitive for data like yours? How does this vary by industry? Empower one partner in a monopolistic environment but use a more diversified strategy in openly competitive markets. One common approach is to segment data that is geographically about a particular region to partners in that region. By combining these two segmentation strategies, you can ensure that your chosen partnerships are protected from interference from other resellers.

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This strategy also works.

Sectors and Industry Segmentations

Depending upon the depth and breadth of your data assets in each area, segmenting your data solutions by sector and industry can be a smart approach. We recently worked with a company that could successfully mine and analyze data about local businesses while ensuring the quality of the data continuously improved. Upon going to market, this company recognized that the legal industry and medical professions had very specific data needs that easily allowed for segmentation. In this way, they were able to secure channel data partnerships with a firm that specialized in marketing solutions to only the legal industry and a separate partnership targeting the medical industry. Segmenting along these lines meant that their own internal sales team was given free rein over all other verticals while the two channel data partnerships could keep control over their respective markets.

Client Size and Opportunity Size

The last approach to data segmentation is to review the size of the prospective customer, or the overall opportunity size of the customer. If a potential customer is global in size or massive in their overall revenue opportunity, you may need a dedicated seller from your own firm to maximize that sale and deliver the appropriate service level. Smaller companies seeking to buy your data, on the other hand, may require or expect less assistance.

When building your channel data partnership strategy, regardless of affiliate, reseller, or hybrid approaches, you should review your current client base and identify any likely segments that can be built into your contracts with partners. Sometimes the segments are obvious based on your prior successes and failures to market your data directly. Choose a sizing segmentation metric that is easy to understand and fair to all parties involved.

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It’s never not time to use this gif.

The point to all of this is that you have options when it comes to creating channel partnerships, but you also have obligations — we don’t call them partnerships for nothing.  Being a good data partner means being clear about goals, consistent with delivery (or distribution) of data, and completely solid on compliance with legal and regulatory requirements.  There’s no partnership on Earth worth being dragged into a massive FTC or EDPS investigation over, particularly given that those investigations will cost you in customer loyalty as well as legal fees.

But if you can identify the right kind of partners and the right form of partnership, you’re halfway there.  Figuring out segmentation strategies is your next task, but it’s one that will not only hone your ability to evaluate the value of your data, it will ensure that you have a clearer and better understanding of your customers and your market.  In other words, when it comes to data partnerships, following the right strategy creates a virtuous cycle that makes your data more valuable, your company more attractive, and your options more open.  Finding a data partnership is something every business can, and should, do — so why wait any longer to get started?

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We’re uh…we’re into this stuff.

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