If I’m making a sale to another business, I want to understand and speak to the needs of their company. That way, I don’t waste their time with content that falls flat. That’s what B2B ecommerce segmentation and personalization attempt to mimic. They watch for behaviors and collect demographic information, then address customers with relevant product offers and content as a salesperson would. While segmentation addresses groups, personalization addresses individuals. A B2B ecommerce site without either isn’t much better than a digital catalog and an EDI.
Ecommerce interactions that are personalized with full-blown artificial intelligence are still a few years away. However, segmentation can shape your user experience to appeal to customers in the same way a politician shapes public policy to appeal to districts. In other words, you address relevant issues depending on the group you’re trying to win over. Defining and delivering unique experiences to those groups, from both a strategic and technological perspective, is difficult but getting easier. The main reason for this is the rise of CRMs as the central hub of all of your channels and systems.
In this article, you’ll read (1) how to connect online behaviors to needs so that you can trigger a personalized experience and content, (2) how your products can inspire personalization, (3) how customer segmentation and automation can save your salespeople time and recover leads that don’t respond, (4) how CRM will play a large role in the future (5) about buyer personas or the core districts that you’re trying to win over, and (6) what technology your business will need and (7) examples of attributes you can use to personalize with Magento and Monetate.
Personalization can be leveraged during the transaction–at the end of the process–to automate special pricing and discounts.
Tie Indicators to Insights
One way to start using segmentation is by finding indicators of different business needs. You can start with a common behavior seen in web analytics. For example, you could create a list of customers who visit your store using Internet Explorer. Next, gather data on their needs by reaching out to them through a survey or personally (phone calls are the best). The call is an opportunity to learn and to show your customers that you care. During your talk, look for commonalities regarding their title, company size, budget, constraints, and needs. Most importantly, ask them what triggered their search for a product.
Now you have a group of businesses that you understand and can identify with data. For example, you may have learned that this group wants an easy way to download and print product specs. Since your site doesn’t offer that today, you would have no way of looking at data in Google Analytics and making that discovery.
Now that you know, you can use personalization tools to add a download button to product pages when the visitor is using Internet Explorer to browse. By showing it only to a customer segment that you know wants the special content, you improve their experience and minimize distractions for other customer groups. To see how it impacts the bottom line, you can test the personalized experience using an optimization tool such as Optimizely or Monetate.
Sometimes the attribute inherently expresses a need, no research required. Those personalizations won’t require intimate customer knowledge. For example, Lululemon knew that many of their customers used Apple operating systems to browse their site. Therefore, they integrated Apple Pay with their product pages, which allowed those visitors to buy with one click. Using personalization, they only showed the button to those using Apple devices.
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Let Product Fit Inspire Your Segments
You don’t have to discover every great personalization idea during an interview with buyers. Sometimes product knowledge is enough to create personalized moments for your customers. For example, let’s say you sell concrete products. Hot, dry, and windy weather conditions lead to soft, chalky results, but you sell a proprietary acrylic seal to prevent that.
You can segment by geography (using shipping addresses) to promote your sealing products to companies in southern and southwestern states with helpful content. Consider timelessness as well. You can email buyers from Georgia in April and buyers from Oregon in June with product recommendations. If you want to get fancy with your data, you can set up weather alerts that trigger an email to buyers experiencing unusual hot, dry and windy conditions. Even if you don’t make the sale, your understanding of their business needs will make an impression.
Segmenting Sales Lead, Automate Content and Make Personalized Recommendations
Let’s say your sales team sponsored a booth at an industry show to find new business. Hopefully, they’ll use your ecommerce site to make some sales on the spot. If you have a long sales cycle, they’ll collect some business cards and one-by-one call or email these companies to explain how your products are a great fit. They repeat the process and continue to reach out, but if they don’t get through, the lead goes cold.
Customer segmentation and marketing automation save your salespeople time and recover leads that don’t respond. You can track each touch, automate personalized emails that go out to specific segments, target them with ads on other sites they visit and give the sales team intel and data on any leads that eventually request a meeting. For example, they may reach out to you about Category X, but they spent considerable time browsing Category Y. That’s something your salesperson can dig into.
The effectiveness of your automated ads, emails, and content will depend heavily on your segments. If members of a segment don’t share a problem that you solve, then you can’t use it to write relevant messaging. That’s why it’s important for your salespeople to ascertain these problems early as they can. Even better if they can tie a problem to an attribute that can be identified later by analytics.
Personalize Upsells and Cross Sells
The data from one sale or contract can give you a world of insight into future deals. Even without ecommerce, any good salesperson will know that if someone buys a set of nuts, they will likely want to buy the same size bolts. Personalization removes the guesswork of the past. In exchange, sales teams will be able to improve personalized product recommendations. You may have a new product to offer, but their browsing habits will dictate personalized email marketing campaigns, more targeted sales calls, and better predictions of demand for inventory.
Create and Name Sub-Groups With Shared Characteristics
Averages Lie; There Is No Magic Bullet
Put the client first. It’s a great, simple motto for any business. You want to give the people what they want, whether we’re talking new product lines, payment options on your website, metric specs on your product pages, or less content and promotions in their inbox. But not every business on your customer list will share the same wants and needs. Satisfying one customer could mean displeasing another. For example, data that averages how many visits a customer makes before buying might tell you that the average customer visits buys from you 15 times per year. However, that might be made up of one group that buys 5 times and another group that buys 25 times.
Instead of making investment decisions based on what’s best for the average customer, you can see how an investment would affect key buyer personas: customer profiles that include buyer needs, goals, and limitations.
The Value of Personas
I like personas. They allow you to segment your customer base across multiple dimensions so they clump into large, manageable groups. For example, your persona might be ambitious senior marketing professionals at medium-sized U.S. manufacturing companies. Not only do those attributes tell me something about the person, I can use marketing tools to identify and target them on the web, social media, and in apps. If I refer to this demographic as Ted, it keeps me focused on the human element. Plus, it’s easier to remember four succinct labels than it is to recall the details of four demographic profiles. Memorability helps get your whole team on board with market segmentation. Since 30% of B2B transactions involve 5 or more people, you may want to start with personas based on buyer, researcher, and decision maker.
When you assign values like total revenue generated and revenue per customer to each persona, it helps everyone understand their relative importance and potential. You can measure features based on their potential to affect TAM and SOM for each persona.
Nobody is going to fit one of these personas precisely, but they’ll enable you to toss most buyers in a personalized bucket they’ll be pretty happy to sit in. You should aim to create two to four buyer personas that cover roughly 80 percent of your clientele. This should be manageable enough for most business models to create a solid buyer journey for each. If you can’t reduce it down, ease up on specificity. Lastly, make sure that your personas are inspired by data. This isn’t a fiction-writing seminar.
Introduce Personas To Your Business Research Framework
Once you have confidence in your personas, you can use them to inspire tests. Here’s an example: You find that one of your personas tends to spend 20 percent more per year than your average customer. When you talked to these customers, they shared that product videos are an essential part of how they research new products for their company. Today, this group makes up a small percentage of your base. You want to attract more of these customers, but you don’t know if it’s wise to hire a content marketer and buy equipment to create product videos. You decide to create a test video for a typical product. You find that users who watch the video are 10 percent more likely to add a product to their cart. You do some digging and find two things: first, new visitors who came to your site after using organic search went up 20 percent; and second, the average order size is 20.5 percent, roughly the same as your persona. It’s likely that those visitors are brand new customers who hadn’t heard of you before. It’s also safe to say that the videos are attracting 20 percent more business from your target customer. A few more calculations (profit margin, product page traffic, video output per month, content marketers salary, etc) will reveal whether or not it’s worth it to hire someone to create product videos, and it all started with a persona.
Importance of the CRM’s Future
Ecommerce platforms, along with other channels and the ERP, have risen to the occasion because sales engine systems are still coming into their own. If omnichannel centers on the customer, then it makes sense that omnichannel should center on a customer technology: the CRM.
If you store customer information in many places, there is a high probability that the data will get out of sync. In an ideal scenario, you only have one place where you store it. The CRM makes sense. For order information, you would use an order management system (OMS) and for product information, a product information management system (PIM). Everything else (besides your ERP and business intelligence) is a channel, not a repository.
These three systems make up the sales engine of an ideal architecture that sits between your ERP and sales channels. In other words, your ERP and ecommerce channel wouldn’t have to talk. That keeps your ERP from having to do things it’s not meant to do. Pulling customer information out of an ERP is clunky. Instead of a bloated ERP system, the data stays clean, and reporting stays fast.
Business Intelligence pulls data from the CRM, OMS, and ERP so that you can combine reports to understand your business better. By running your reporting out of a data warehouse that extracts every hour, you maintain fast performance.
The Sales Engine
The process for omnichannel is integrating new channels with the sales engine. All personalization would pull from the CRM, OMS, and PIM. All customer-facing channels, salespeople, marketers, and ecommerce systems, would pull from the same place, and likewise, they would send customer data back to the CRM to be used by other channels. No matter what channel the customer is on, they get a personalized experience based on every click, tweet, call, order, and wish list item, salespeople have they talked to, average order value, most visited product and category pages, email opened, and stores visited.
OMS, PIM, and CRM Examples
You could also base personalized product recommendations on OMS data to meet business needs. For example, you would know if a distribution center has excess inventory, and which companies have shipped similar products to that area.
PIM is mostly an outward, read-only data set, but that could change with the rise of user-generated content. It’s easy for marketers, salespeople, and reps to pull images that were created by customers to optimize offline and online sales.
CRM-centering improved the customer experience in ways not related to personalization. For example, if a customer calls to amend their order, a customer service rep can go into the CRM and change it so that gets reflected in the OMS.
The path starts here
If you use your imagination, it’s easy to see that the systems and tools we have in place today create a subpar customer experience. No one is omnichannel because we still have systems per channel. We want to build the optimal customer experience, but the technology is not where it needs to be. By investing in so many systems, merchants box themselves into a corner. While you can’t build the optimal experience today, you can spread yourself out and make life harder for your future self, or you can begin to consolidate data in your CRM.
Getting The Right Technology
B2B marketers like me have it easy. This site is built on WordPress. Integrating segmentation, personalization, and marketing automation tools is a cinch compared to the path in front of you. Ecommerce requires integrations that make everything more expensive, complicated, and slower. However, you can’t let that stop you because it won’t stop your competitors.
If you want to personalize, my first bit of advice is to implement a CRM. Second, build your site on an ecommerce platform that includes some segmentation and personalization functionality. Any serious ecommerce platform company is trying to get better at it so that it can attract and retain marketing-savvy customers. In a way, as their customer, you and other companies crowdsource machine learning. When they release updates, you benefit.
Second, look into personalization software. Personalization is limited by the number of attributes you can use and tools like Monetate expand your list dramatically. You can see which will best cover gaps in platform functionality and offer A/B testing abilities. We’ve listed the available attributes from Magento and Monetate in the section below. You don’t want to pay for tools that you won’t use. A personalization tool is an excellent phase 2 after you implement a site.
Third, find marketing automation software that integrates well enough with your CRM. I have a friend working for a Fortune 100 company who has wasted 3 years vetting marketing automation options. Meanwhile, the competition has 3 years of data and multiple campaigns they can run anytime. My opinion: they are all simultaneously delightful and annoying, so just set a deadline and pick one.
If you want help sorting through the options, a digital agency will happily talk you through your technology options and make introductions just to speak with you.
Lastly, Blue Acorn works with two ecommerce platform partners. Both companies offer solid segmentation abilities and have for years, but only one is killing themselves to attract B2B customers. When Forrester said that the market would grow to $1.1 trillion by 2020, I believe that lit a fire under Magento. They have an enormous B2B customer base and a decade of functionality requests from B2B merchants. The newest Magento Commerce upgrade includes new B2B features, which have been a long time coming and the list is everything we hoped it would be. You can check out our take in a blog article we’re releasing next month (wouldn’t want to spoil it).
Magento and Monetate Attributes For Personalization and Segmentation
If you’re interested, here are the customer attributes you can use to segment customers in the Magento Commerce (formerly Magento Enterprise) admin panel:
- Customer – customer address, name, email, newsletter subscription status, and store credit balance
- shopping cart – shopping cart quantity (line items or total quantity) or the value (grand total, tax, gift card, etc.) of the cart contents
- Product – products currently in the shopping cart or wishlist, or that have previously been viewed or ordered. You can also set a date range for when this occurred. The products are defined using product attributes.
- Order information – Order characteristics for past orders, the total or average amount or quantity of the orders, or the total number of orders. You can also set a date range for when this occurred, and the order status of the orders that match these conditions.
Some of those attributes will require customers to log in, which you can incentive in many ways including loyalty programs.
Using Monetate, here are the attributes (target types) you can use to personalize the experience:
- Location – by city, state, distances to certain addresses or addresses, time zone, language, etc.
- Landing page – referrer, search terms, new visitors (vs returning)
- Weather – current or forecasted temperature, wind, rain, etc
- Behaviors – brand in cart; brand/product/category in cart, last purchased, purchased, viewed; time on site, quantity, sessions in past seven days, etc
- Technographics – device type, browser, screen height, operating system, etc
- US demographics – age, income, population density, voting patterns, families with children, etc
- Names Segments, Custom Targets, and Datasets
When designing a personalized experience in Monetate, you can also define when you would like the personalization to take place (start and stop date) and what metrics you would like to track (bounce rate, revenue per session, cart abandonment rate, revenue per session, new customer acquisition rate, etc).
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