vNalytics Dashboard — Turn mobile number databases into gold mines, without hiring any additional human resources.

Background

In any B2C high-value company, the biggest challenge a marketer's faces are that he/she wants to generate enough leads(potential customer) but also want his/her team to spend enough time talking to the high-quality leads ( an ideal customer prospect).

Now to get the full control of the number of leads, marketers use outbound channels like email and SMS campaigns.

Primarily in India, SMS has been the most popular medium in marketing campaigns.

Without spending too much money or expanding the team, how can the marketer identify all the people who fit their ideal customer profile within the phone number database?

Research

Primary research was conducted by product owners. They shared their findings with me and answered my questions. I am sharing the finding which helped me to make decisions.

In most SMS Marketing campaigns, lead generation has relied on people taking initial actions like calling on the given number or filling up a contact form.

This system is based on a huge assumption that everyone who is even partially interested will call back or fill up the contact form.

People are often reluctant to contact salespeople until they are sure that they are very much interested in buying. This kind of clarity is hard to achieve from just text SMS and some content.

There is a huge amount of information loss from marketeer’s side because unless the prospect contacts them, they have no way to know whether the person who opened the link was interested or not or was just reluctant to call.

My Role

I designed the product! With the help of product owners in research and critique, I solved product design problems. I also delivered low and high fidelity wireframes along with interactive prototypes.

Solving the Problem

Eliminated inquiry forms with unique links in SMS

The first thing we wanted to do was to free SMS receivers from filling up painful inquiry forms.

We decided to embed a unique link with each SMS. When the receiver opens this unique link, he automatically gets registered as lead and the marketer is notified on the dashboard that this person opened the link.

Bulk SMS service providers also had a similar feature but at a limited scale, hence we had a really nice opportunity in this domain.

Filtering leads automatically and effectively with a chatbot

We wanted to spare marketing guy from doing that same conversation to qualify a lead, but we also wanted that interested person gets enough information upon opening SMS.

I saw that intercom-operator and drift have solved the problem of redundant conversation. Bots in a similar situation have worked well so far, I suggested to do an experiment with that solution.

We also thought to build a similar feature. In vNalytics marketeer can create the Chabot conversation based on their current conversation scripts and also give multiple response choices for the receiver.

This helps the receiver from putting extra effort to think and type. It also helps marketeer to drive the conversation.

(for mvp, we just took the script from our clients and converted into chatbot conversation from the backend, we did not create UI)

The goal of chatbot is to inform & attract people and lead them to the sales process.

If a person is interested and gives a positive reply to certain decision making questions, such as booking visit, he would be marked as “hot lead” or “warm lead” based on the replies. That’s what marketers call most interested prospects and partially interested prospects.

Rather than the conventional chat-window layout, this layout is less intruding. To make it visually pleasing I used micromotions.

Now marketer knows after whom they have to actively follow up, without investing the time of a human resource!

Dashboard designed to increase the productivity of marketer and increase the efficiency of the campaign.

We created a dashboard to capture information gathered by chatbot in one place. It also displays who opened your link, how many times and for how long.

To save the marketers from jumping from section to section, I designed the dashboard in a way where all important elements of the campaign get displayed in just one screen.

Different teams have different processes for following up prospects. Hence, primarily I display all the hits, one can always filter it out to see what is important to them.

Online Customer Indication

If a person gives consent to contact, the marketer can immediately contact him. According to research, contacting the person right after they have gone through your content increases the chances of sales manifold.

Hence I added a quite noticeable green patch so marketer does not miss a single important lead.

Lead Types

There are 4 types of leads based on the conversation they have done with the chatbot.

We used the marketing jargons to make it easy for marketers.

Hot & Warm leads are most commonly used by marketers to depict the interest level of a person to buy their offerings.

I used simple small badges as cues to make it faster to understand who is hot lead and who is warm.

Activity Timeline

Activity timeline of the person gives the marketer the idea that when and how many times a person opened the link.

This is especially very helpful when a person has not given the response but opens link many times and spends time on content. In this case, the marketer sends the message again and try to persuade to talk.

This is very important for high-value products as even one sell from a campaign can be quite lucrative compared to campaign cost. So, marketer tends not to miss even a small hint towards a good lead.

Monitor multiple campaigns at the same time and get quick info on outcomes.

In some firms, campaigns were as frequent as 2–3 campaigns per day and in some once a week. So there was no fixed number that how many campaigns should be displayed at once.

Hence I decided on a median number and displayed 10 campaigns on navigation bar maximum and rest can be accessed from the list of campaigns.

CSV download support for people who make reports.

The marketer also has to make reports on how successful their campaigns were. 90% of them make reports in excel or similar tool. Hence we supported to download a CSV file of all hits they get, campaign and leads addressed by each team members to make their reporting task easy.

It also helped them to send SMS to retarget the responders.

Fixing scalability issue

Over the period of time, there are going to be too many campaigns. Projects will be added as well. Hence we designed the dashboard keeping in mind that we should be able to accommodate data of at least 2–3 years of company data right now before we improve the design to support even larget scale.

Team management and distribution of leads

We also facilitated the distribution of leads among the team members, to ease the follow-up assignment problem, like who will follow up whom.

I chose to allocate leads to the marketing team members automatically, but there was a problem.

Marketing team does not sit in front of computer watching campaign analytics whole day. Team members keep changing based on their involvement in other projects and activities. Hence to co-up with that, I provided an option to turn off the auto-allocation and distribute leads later.

So, By default allocation is automatic, but marketer can turn it off and later distribute to available members as per availability of his team members.

This would give him full control of the lead and follow up the assignment, as per his team’s schedule.

Outcome & Impact

With vNalytics our clients increased the lead generation by 10 times, without spending any extra human resource.

With Godrej Properties, On an average 35 out of 100 people who clicked responded. About 10% of them were warm leads and about 7% were hot leads means they committed that that will come for a visit.

vNalytics proved to be lucrative. Salespeople from many big firms such as Godrej Properties, Club Mahindra, Mahindra Lifespaces, Mahindra Automobiles, Lodha Builders uses vNalytics.

Here is the prototype link for you to see vNalytics more closely.

Prototype Link