Aberdeen recently found that only 15% of organizations have mastered the ability to understand their clients and address their needs effectively. With that in mind, Aberdeen released a checklist of the key capabilities that allow successful organizations to create truly impactful buyer experiences. To get a better understanding of why all of these capabilities are so powerful, you must first understand the key characteristics of high quality data.
Do you have all of the information? If half of your opportunities only have the minimal attributes recorded (e.g. Company name) and are missing the fields that make them easily grouped with similar opportunities (e.g. employee count, estimated revenue, industry) you’ll find yourself with plenty of data, but no real intelligence. If your sales reps aren’t recording all of the calls, emails, and meetings that they perform every day, how can you possibly make any conclusions about what activities are actually helping to close deals?
The data that you’re reviewing should be relevant to the goal you’re trying to accomplish. In the sales world, this is especially important because the last thing you want to do is burden your sales reps with recording information that serves no purpose. You could have your sales reps record what they have for breakfast and lunch each day and try to associate that to quota attainment, but chances are that any correlations you make are purely circumstantial. (Sorry Wheaties, I know you’re the breakfast of champions, but we need information that’s a little more on target!)
Along with being complete, data must be consistent. For example, you have one sales rep who records the number of employees in groups: 1-50, 50-100,100-500, 500-1000, etc. You have another employee who records employee counts with real numbers: 562, 11,500, etc. You’ll spend far too many hours cleaning up these inconsistencies that may seem minor at first glance but make compiling information impossible. Another example, what makes a Sales Qualified Lead? Is it an opportunity that you’ve had a meeting with? Is it an opportunity that meets the BANT requirements? Is it a lead that agreed to go golfing with you every Sunday? Everyone must have the same definitions when entering data.
The data you have must be current. This is especially important in the world of B2B sales where the ground is trembling under sales reps’ feet. Buyers are constantly changing, their behaviors are rapidly evolving, and only the most up to date information will do. What good is it to know who your top accounts were five years ago if those accounts now have new reps, have merged or split, and the product you sold them isn’t even supported anymore?
The final feature of high quality data is accuracy. Are there typos? Is the contact information still correct? Is the revenue amount for that newly closed deal correct, or is still set to the best guess estimate from when they entered the pipeline? You might think this a no brainer, but Sirius Decisions found that as much as 25% of marketing data is bad.
So now that you have a basic understanding of what makes data high quality, let’s take a deeper look at what makes up a best-in-class customer intelligence program:
Integrate all enterprise systems involved in capturing customer data in order to form a unified view of the customer journey.
Integration of all of your data collecting systems is key to having complete data, but so many organizations have their data spread out far and wide. In order to gain insights from the data being collected, researchers must dig through disparate databases, compiling, merging, scrubbing. By the time a complete picture is created, the data is no longer timely.
Regularly analyze customer experience data to identify process bottlenecks and inefficiencies.
It’s important to know how your buyers are moving through the pipeline, which stage do they usually stall out on? Does it take 3 weeks for a proposal to be sent out because every proposal must go through 5 rounds of validations and approvals? Does it take a week for a sales rep to respond because they have to search through 10 different repositories to find that perfect piece of content? When you consistently track every activity performed, each stage duration, and accurately mark lost deals as lost when they are lost (not 7 months later during your annual spring cleaning) you’ll be able to gain valuable insights into where your sales process can be improved.
Align priorities of the IT team with the rest of the business by compensating the IT team based on achievement of objectives supporting customer experience programs.
Chances are the I.T. department is going to be doing the heavy lifting when it comes to setting up your customer intelligence ecosystem. It’s important that you clearly communicate to them what your goals are, what metrics are important to you, and what is a reasonable timeframe for receiving the information you need so that they can ensure that the data they provide meets all of the quality requirements. When you make them a stakeholder in the success of the customer intelligence program, they will be more receptive to your demands.
Provide employees with a role-based view of customer sentiment and behavioral data.
Don’t give your employees information overload. They should only be seeing what is relevant to their specific needs. A marketing manager should know what content is effective in moving deals forward and what campaigns are bringing in high quality leads. A sales rep should know what opportunities are most likely to close and which piece of content has the most impact with buyers matching a particular industry, persona, or specific business challenge.
The remaining items all fall under the category of completeness. The more information you have, the more awareness you’ll create and the more insights you can gain.
Distinguish most profitable clients from the less profitable.
When you integrate your accounting and support systems with your sales and marketing systems, you get a clear picture of how much revenue a current client is bringing in, and what upsell opportunities might exist. When you have enough information, you can begin to make assumptions based upon particular segments – like which vertical is more likely to spend the most amount of money with the least amount of support hours.
Regularly monitor and analyze customer referrals to assess earned-media results.
There’s nothing better than a referral that you don’t have to pay for. Customer referrals are not only usually free (sure you can provide incentives, but if your product is good enough your customers will be happy to spread the word without the need for compensation). Not only does that save you money, but when you have an unbiased customer voucher for you, chances are the deal will close faster because you’ve already earned the prospect’s trust. Look to see where your best referrals are coming from and then try to expand those relationships as much as you can.
Use behavioral data to identify factors influencing cross-channel buyer behavior.
Most companies do not just stick with one advertising medium. You have inbound campaigns, outbound campaigns, nurturing campaigns. You might advertise on PPC, television, and event sponsorships, all at the same time. A prospect will typically interact with your brand on multiple occasions before they take that big step towards starting a conversation with your sales team directly. It’s important to understand how your buyers find you and how all of these channels work together towards a cohesive, seamless customer experience.
Benchmark performance of all customer interaction channels.
Just as it’s important to know how all of the different channels work together, it’s also important to know how one channel performances against others. Are you wasting your precious marketing budget on a channel A that brings in the same amount of quality leads as channel B, but costs 300% more per lead? You need to be able to understand not just how many leads are generated by a certain channel, but also how those leads then perform throughout the entire sales pipeline. Sure that marketing campaign brought in 1000 MQL’s, but only 10 of them turned into SAL’s and none of them ever closed. Without that kind of intelligence how can you possibly make the best decisions as far as strategy?