Category: Analytics

Guest Post : The CRM and the pre-contact data challenge

I recently faced a data challenge that almost disturbed a whole organisation. My aims were honorable, I insist, but this was something so new, so unprecedented that it nearly didn’t happen. When it did, it revolutionized the marketing to sales hand-off, and a number of processes in between. It gave us an extra layer of rich detail that enhanced our marketing and sales processes, with market information that gave us real focus.

Stage 1 – get the data

There are a host of IP tracking software programs available, some better than others. We selected one which provided a short piece of code to put on our website, which tracked the IP address of the businesses surfing our website, and matched them to Dunn & Bradstreet databases, as well as LinkedIn. Immediately, we had a flow of data; from the 1500 visitors who hit the site each day, we could identify at least 300 of them. The system would give us key contact data from LinkedIn – in our case, we wanted the Human Resources and the Finance Directors, as well as managers.

However, it would also give us an extra rich seam of data to work with – what pages they were looking at, which search terms they had used, how long they had been on the site, and how many times they had visited in total. These metrics allowed us to gauge their level of engagement with the website, but also what they were interested in. When a leading airline came on looking specifically for what we provided, we knew there were something powerful here.

Stage 2 – filter the data

What we quickly realised was that the data we were getting through was of huge value, but only if we were able to quickly filter through it for opportunities. We extracted our own database into .csv format and filtered that into customers, prospects (i.e. leads) and suspects (i.e. no contact has been made). Within customers, we broke that up into international, safe and at risk, so that we could better understand why our customers were on the website.

That data was then uploaded into the system with a match against business name, and each organisation was then tagged appropriately. Naturally, data sets include variants, so a secondary match was made for those with no match, against the business address, in order to ensure that as many of the organisations as possible were tagged. We used a colour-coding system to quickly identify our web visitors.

Stage 3 – identify what matters

We set up a steering committee to understand exactly what we wanted to get out of this data, and how we were going to use it. For the first time, we were able to identify when a potential lead made first contact – but we needed to identify exactly what we required, and how we would use it.

Clearly, search information was key – this gave us an idea of the user’s intent. In one instance, we identified a leading hospitality chain before they went out to tender, knowing exactly what they were looking for before they told us. That allowed us to approach them. Therefore, matching a business name to a keyword was crucial.

Engagement metrics were equally key – we didn’t want to know a business who had left after just one page, or one that had not returned. Therefore, we needed to filter the data into the “most engaged” businesses, using number of visits, number of pages, and equally using triggers to see businesses who had visited certain pages.

Stage 4 – set up the CRM to drive the project

We were using Microsoft Dynamics CRM, which allowed us to create bespoke events that would be visible in the 360 degree dashboard. Of course, this would have to be at organisation level, as IP addresses cannot be matched to contacts directly. What we needed was a new “web visit” event matched against organisations, with key information such as keyword, titles of pages visited, depth of visit, total number of visits.

Rather than setting triggers up in the tracking software itself, we used the CRM to automatically trigger an alert to the appropriate business development manager whenever a web visit was triggered in the system. So, for example, if a business of 500 employees in the South-East recorded a 6-page visit on a key search phrase, then the South-East mid-corporate business development manager was alerted.

Stage 5 – getting the data back into the CRM

The key here was automating the process – and required a little bit of trickery in the background to ensure that it worked seamlessly. On a daily basis, the system would do a batch data upload into the CRM using a cross-match of data fields that transferred vital information from the tracking system online, into the CRM.

Equally, where contacts were missing from an organisation, we would receive an alert that would allow us to manually update the contacts ourselves at a later date.

Stage 6 – getting buy-in & refining the process

There were bound to be initial problems – for example, some sales representatives resented receiving too much information about potential prospects they had no interest in. However, upon receiving the aforementioned tip-off about the hospitality chain, a salesperson decided to act, and was able to use the search phrase information to build a conversation with the business.

Sales agreed that it was best to collect data over the long-term and get a better appreciation of the prospect’s buying process. For example, contacting the prospect too soon in the process could potentially be a negative – the CRM was throwing up extra intelligence that showed prospects were likely to visit the website at least five times before making an enquiry. What we needed was a trigger to say “this business should have contacted us by now” – and that was when we had to act.

Stage 7 – building intelligence into marketing efforts

Events and triggers from the Dynamics CRM allowed us to better inform sales of when a potentially sales-ready prospect had been on our website, but there was a further layer of information that we could use here – the pre-contact buying process. We had learned that contacts were using key phrases of a generic nature in order to find out about the service in general, and then they were diving into deeper information, with white papers and PDF downloads being crucial at this stage. At a later date, they would return with a brand phrase – either brand alone or brand + service.

We could then take this information to make a soft contact with the organisation, either by direct mail or telemarketing, in order to gauge their true level of interest. We would never mention the fact that we knew what they had been looking at (it sounds a little big brother!), but our conversion rates on direct and telemarketing rose substantially as a result of this intelligence.

The CRM allowed us to extract data according to most recent visit and number of visits to the site, and we could then prioritize our efforts according to depth of visit and keyword intent, personalising the message further. The additional data provided by the system, cross-fed into the CRM, allowed us to further enhance our contact possibilities.

And at the heart of this…

We believe that CRM is the cultural glue to an organisation. You only get out what you put in, and that was the mantra that every department in our business repeated – from the quality of the data, to the depth and richness of that data. By adding in a layer of pre-contact intelligence, and looking at the models of engagement with our website, we were able to build an observe-and-contact model that both sales and marketing could use in order to better understand and approach a potential prospect with a view to getting a face-to-face appointment.

As we go on, we are beginning to weave new aspects into our contact strategy, from building in social media feeds to getting a greater appreciation of customer needs. For example, there is potential for upsell when a customer visits the website, looking at extra product or service pages. We did not have that capability before because it was not spoken.

At the very heart of this, was the CRM. The glue that binds the organisation, the tool with which to interpret and communicate this intelligence, and drive what ultimately became a stellar year for sales.

Gareth Cartman

GarethCartman Gareth Cartman writes frequently on business, HR and CRM topics, and works with MS Dynamics partner Preact, who are based in the UK and were recently awarded President’s Club status by Microsoft.

CRM : Look beyond numbers

Few days back, I got a marketing call from my mobile service provider, they suggested a new bill plan for me. It was very attractive, lot of benefits when compared to my current plan, and the price was also reasonable (Rs 1000).

So, I decided to shift to this new plan and gave them my decision. I got an SMS immediately, everything went smooth. I started enjoying all the new plan benefits, and felt happy about the right decision.

One month later, yesterday I got the bill and it was a shocker, because, it had Rs 2000 as the plan cost, instead of Rs 1000.

I am sure all of us would have faced this kind of a problem before, we would dial the call center, shout at some helpless lady there that the company has cheated us, threaten them that you will go to court and finally, (if lucky) get the refund back. This post is NOT one such story, believe me

My intention is not to share my frustrations with you or throw dirt at the mobile company (That’s why I am not even mentioning their name here). Instead, I fully understand that such service issues can happen at any company, and want to think aloud on what is the best way to handle them.

Coming back to my story, I immediately contacted their call center, informed them that they have charged me Rs 2000 instead of Rs 1000 and asked for a refund (and reason). The gentleman on the other side of the phone was very kind, apologized for the error, took just few seconds to understand the real issue, and gave me a solution almost immediately. (May be many people are facing the same problem!)

Actually, the plan to which I subscribed to, is called “Package 2000″ (or something similar), which means, the fixed rent on this plan is Rs 2000 per month, and then, they enable something called a “50% discount package” on top of it. As a result, you will get Rs 1000 discount on your bill every month, bringing the effective rent to Rs 1000 only.

In my case, they never told me about this complexity, and simply sold it as a “1000 Rupees package”. Technically, it is not cheating, but they should have mentioned it clearly during the “Marketing” phase.

OKay, Marketing is done, I am ready to buy the package, at least now, someone should have told me that the plan is actually called “Package 2000″ and I would have asked “Why 2000?”. They missed this step too.

Biggest mistake, they forgot to enable the “50% discount package” for me. As a result, I got a bill for Rs 2000 now, instead of Rs 1000.

The call center person could revert it back to Rs 1000 very easily, and enable my “50% discount package”. I am happy, I even gave that person a “5/5″ rating as the feedback. But, the bitterness is there with me, that they didn’t handle this right.

What they could have done differently?

  1. They could have created a simple “Package 1000″, instead of a complex combination “2000 Package” + “50% discount” (Owner : Product Management / Marketing)
  2. Even otherwise, They could have told me clearly about the package, instead of selling it to me as a “Package 1000″ (Means, you are hiding facts about your products to your customer, just to make a sale) (Owner : Marketing / Sales)
  3. They could have put a process in place, to ensure that “2000 Package” always goes with “50% discount” package, just to make sure no customer gets a surprise after their first bill (Owner : Delivery / Deployment / Billing)

These are the “Expected” reactions, if they want to go one level up, they can “surprise” or “delight” the customer by taking few more initiatives, but that would be too much to expect at this stage 🙂

Now, let us analyze this entire story from a Customer Relationship Management standpoint, these are the transactions, and the result:

  1. Marketing call to customer : Success
  2. Sales to customer : Success
  3. Delivery of the product (package) : Success
  4. Customer raised a complaint about Billing
  5. Customer complaint resolved in 2 minutes : Success
  6. Customer gave a “5/5″ rating : Super Success

Do you see the problem? My mobile service provider will NEVER know that things went wrong in my relationship with them, they will never know that there are number of improvement suggestions they need to work on, if they just look at the statistics above. Unless and until I write a long Email detailing all these to their senior management, they will be under the impression that everything went smooth. Even after I write one such mail, there is no assurance that action will be taken against it.

This proves beyond doubt, that CRM is not just transactions, it is the overall relationship that matters. If you just look at the customer records / activities / feedback numbers, you may be missing the real picture altogether.

There is a very famous quote about statistics, let me borrow it and modify it slightly : “CRM systems and reports are just like mini-skirts, they give you good inputs, but hide the most important things!”

Naga Chokkanathan

Senior Director, CRMIT

Originally Published in

Oracle Fusion CRM Reporting

Oracle Fusion CRM comes with a comprehensive Reporting Module, which is very easy to use, flexible, yet powerful enough to capture all your reporting needs.

If you are already comfortable with Oracle’s BI (OBIEE Or CRM On Demand Answers) way of creating reports, this should be very easy for you, there is basically not much to unlearn / relearn as you can see from the steps below:

Step 1 : Go to “Navigator” > “Tools” > “Reports and Analytics”

Step 2 : From the left navigation, click on “Create” Icon, It opens a popup screen

Step 3 : Select your Subject Area, Reporting Wizard Starts

Step 4a : Select Columns / Organize them as per your requirements

Step 4b : Name your report, Select Views (Table / Chart / Both), Decide on the layout

Step 4c : Edit Table

Step 4d : Edit Chart

Step 4e : Filter your records (to display limited information in your report), Sort them based on one or more fields (Ascending / Descending)

Step 4f : Define Conditional Highlighting (If any)

Step 4g : Define Location : My Folders / Shared Folders / Subfolders & Save

Step 5 : From the left navigation, Click on the folder specified in Step 4g, Click on the report name, Click on “View” to view the report, Or “Edit” to edit the same