As I had promised in my previous post, I start today’s post by explaining how an Enterprise can operationalize analytics.
The biggest challenge for any Enterprise, whether B2B or B2C, is getting to know its customers.
This is the first of the six essential steps in operationalizing analytics for any company, and it is often where many falter.
But before you go down that road, you need to analyze your company’s products or services, to get answers to:
- How will I sell my products/services?
- Who’s interested in buying my products?
- (More importantly) Where do I sell?
- Where are existing customers buying from?
If you think that drawing a customer profile is a simple matter of clubbing clients under generic labels like, ‘Men, aged 30-40 years, or ‘Firm with less than the US $50 million annual revenue’, well, it’s not so.
Such simplistic ‘profiling’ of your customers is not enough. Why? Not all men in a particular age bracket have the same spending power, for example.
Thus, your company cannot afford to draw up “half-baked” inferences about your customers.
Know how to build a Customer Profile Database. Identify all your customer touchpoints and consolidate the data. Speak to Our Experts
There’s a simple mantra behind building a customer profile base: draw up as intricate a profile of the customer as possible.
A lot of effort has to be put into understanding customers:
- Ascertain all your customer touchpoints and assimilate the data
- Using this data, calculate the value of each customer, i.e., what does he cost your company to acquire and retain, and what kind of revenue do they contribute?
- Then, profile your customer base to establish the characteristics of your ‘most valuable customers
We, at Express Analytics, for example, deploy a variety of analytical techniques to decipher customer data collected from social media, emails, geo-location, and across channels and devices, to help enterprises identify who their customers are and the value of each.
Social: We believe social media has become one of the most critical data sources.
Start by appending the Twitter handle, Facebook account name, and WhatsApp account to every customer’s database account.
Then, build in an automated signal that alerts the company when a customer uses specific ‘keywords’.
Also, every time a consumer ‘likes’ something on Facebook, it must trigger an alert. By analyzing a consumer’s social journey across multiple social networks over a period of time, a clear picture of their likes, dislikes, and even spending power can be ascertained.
Emails: Email analytics is another valuable source for building a credible customer database.
First, our dashboard tracks every aspect of an email – including the number of bounces, the number of emails opened, links clicked, and the ‘unsubscribe’ behavior.
It is also necessary to integrate data from other email service providers used for email marketing strategies, such as MailChimp and SilverPop, for your customers.
Discover which types of emails resonate with a particular recipient by analyzing their email analytics.
Channels: Identify the channels through which customers are purchasing your product or service.
Channels refer to the various methods customers use, such as a browser, Twitter, WhatsApp, email, or SMS. Tie in all the data with the customers’ profiles.
Devices: Identify their device preferences, whether they are desktop or laptop users, primarily using their devices on a desk, or are they mobile users.
Desktop, mobile, Android, Windows, the apps they use…and so on.
Operating Systems: The various operating systems used by the customer in the process.
Windows, MAC OS, Unix, Linux, iOS, Android, etc. Each can allow you to offer different levels of personalization and customization, thereby enhancing the intimacy between the customer and the brand.
Third-Party Integration: Integrate customer profiles obtained from third-party consumer data collection companies, such as Datalogix, and agencies like Nielsen, Experian, BlueKai, and MasterCard, as well as e-commerce engines like Magento.
Build a Customer Context: Develop a detailed database of your clients, capturing all relevant information about them, including contacts and conversations.
Collect a lead’s life events, such as birthdays, marriage anniversaries, divorces, vacation plans, movie outings, weekend plans, wish lists, marital status, children, zip codes, income bands, educational degrees, shopping habits, and preferred stores.
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Customers may also be grouped by similar psychographic variables such as values, beliefs, buying patterns, and lifestyle choices.
Demographics: This is the simplest step in building a customer base profile.
Customers may be grouped by similar variables, such as age, gender, occupation, education, income level, geographic location, industry, number of employees, years in business, products or services offered, or other defined criteria.
Thus, having successfully built your customer profile database, the next step in operationalizing analytics is creating a Prospects List, which is the subject of my next post.
