For efficient email marketing that delivers results, it is imperative to get audience selection right. For Technology companies this becomes even more critical given that the concepts are often not straightforward to communicate and require a fair amount of contextual knowledge on part of target audience. Consider a consultancy that sells IT solutions for measuring customer lifetime value. Such solutions would likely appeal far more to clients running subscription business as opposed to media publishers or public sector firms. However, most leading B2B databases provide a very high level company classification in the form of SIC or NAICS codes. How do you target a prospect in a SaaS business while leaving out the ones from other categories even though they all have the same SIC code, number of employees etc.?
This is where secondary classifications come in. In this article, we outline 3 such classifications that we regularly help setup for our clients over and above the regular meta data around revenue, employee count, SIC codes etc.
Business model
For targeted email marketing, we define 4 business models in our classification.
- SaaS – Online businesses with recurring sales. E.g. online libraries, subscription software, paid membership sites
- Ecommerce – Online businesses that sell retail items online. E.g. snapdeal, myntra, Homedepot, Currys
- Media Publishers – Digital publishing houses such as news outlets and niche community networks. E.g. Newyork Times, Techcrunch, CNN.com, ESPN
- Services businesses – Companies that sell products or services with extended sales cycles. E.g. Infosys, Cognizant, Serco, Accenture etc.
Adding sub-classifications on the lines above allows companies to develop highly targeted personas for personalized marketing. For example, a business intelligence consultancy could offer marketing attribution measurement services to Ecommerce and SaaS companies while making a pitch for digital inventory monetization services for media publishers. Without the business model level classifications, it would not have been possible to do targeted campaigns given that it is entirely likely that a SaaS company may have the same SIC code as an Ecommerce outlet.
Product company vs. Agency vs. End client
A simple query in a B2B database using common factors like revenue, employee count, geo etc. may result in thousands of entries. For Technology Companies these lists are pretty much useless. A Technology company selling chatbot software will most likely not want to target its own competitors or other consultancies. A technology outsourcing company providing product development services may only want to target product companies of certain size.
All these targeting options can only be enabled if there is an overlay indicator that specifies if a company is a technology product company, an agency, both or just simply an end consumer.
Industry sub-vertical
For advanced targeting, it is helpful to know industry sub-segments. For example, different service/product offerings maybe designed depending upon whether a particular retail customer is focused on or more retail sub-segments such as electronic goods, fashion, beauty, healthcare, fitness, travel, leisure, cooking and so on. For insurance services vertical, sub-classifications could include products/services for insurance in health, life, property, vehicle, travel, and high value goods.
Armed with knowledge of sub-verticals, marketing teams can create highly engaging uses cases and other marketing collateral that zeroes in on specific technology use case and thereby generate maximum interest among target audience groups.
Summary
Targeted marketing requires a deep knowledge of customer context along multiple dimensions. Standard B2B databases rarely provide granular classifications beyond SIC codes, revenue etc. given the diverse needs of individual users. Yet, B2B Marketing teams must strive to develop internal capabilities or third-party partnerships to help create effective classifications for proper messaging. We maintain that particularly for B2B Technology Marketing, these investments should take priority over budget commitments to other tools and technologies that essentially play the limited role of delivering messages to chosen recipients.
