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Every time something new comes up and people jump on it, they learn something new but it seems that they often start forgetting the best features of the previous while learning. Then came the content marketing era and inbound marketing surge. Now there is a swing back to ABM (Account based marketing and proactive sales). Danny Wong from Blank label just published an article about this with 9 B2B sales predictions for 2016 in Huffington Post (source: http://www.huffingtonpost.com/entry/the-future-of-sales-9-b2b-sales-predictions-for-2016_us_56beb9b0e4b06fb6526b67c9)
It was great article and I totally agree with Mr. Wong.: Outbound and account management are musts, buyer journey and customer centricity are imperative. Marketing automation is fantastic in existing customer management and content marketing. Still, in case of new prospect recognition most visitors don’t leave their contacts or signs of interest which leaves most potential customers unrecognised. This is something that has bothered me.
Then I learned about Leadforensics… (because they reached out to me and outbound works 🙂 ) They gave me a short introduction to their software (phone+video), we did a pilot with two weeks of data capturing after which they presented me the results and pitched me an offer. I got hooked and bought the license.. and I am even more hooked now. (By the way, their process is very much worth experiencing too, its brilliant. You can book your trial contact here)
This is something I just have to share, because I find Leadforensics to be so elegant, easy and effective. The foundation of the service is IP address recognition. The service lets you know from which companies people are visiting your website, how many of them, which content, time spent and so on. In B2B this intelligence is often enough. You know which companies are looking right now in your sector and they are already considering your company. In case you are considering marketing automation or need leads for sales to follow, Leadforensics is a great tool to take as a first step in operational and cultural change or as part of the lead generation development in marketing automation project. This is what you get (this data is from this site):
#1 Visiting organisations
#2 Sorting visitors
Example of multivisitors
#3 Company details and visitors
In this case 3 visits by one person
#4 Potential people to contact
#6 Sorting and actions
Now that I have the tool in use, I can upload my customer register and create a current customer group with assigned contacts. I can also create prospect list with assigned persons who will be notified about new visits. You can also define goals, not every content is a sign of buying intent, but some are exactly that. Assigning goals and actions for them is quite easy and effective.
My company FutureCMO – Catalyst for Growth is a super temp one man show with a network of other entrepreneurs and I am mostly helping large companies with their digital and customer experience transformation. My challenge is, that projects are large and take my time while running them leaving me little time for selling next cases. When they end I can easily drop between projects. This kind of transformation work is quite time sensitive and frequency of doing it is rare. Also, The lead-time from interest to project could take a lot of time too. Another challenge has been, that I have a globally competitive knowledge, methods and approach, but my work has been local sofar. Now I am going to make my first attempt to get my first very own international clients onboard. While working for WPP and Omnicom this was natural, but as an entrepreneur now it would be a big leap. This is why I think Leadforensics will help me target right companies at the right time and make certain that I can get my projects in without long stand-by periods. I am also working on a start-up for which we are raising money to get started and knowing which companies are interested in our pitch is very important. I am only in the beginning of using Leadforensics, but I am quite impressed with it.
In case you find Leadforensics interesting, you can book your own demo and trial period here (Link URL )
In case you are using some other tools for lead recognition, I’d be very happy to hear about your experiences!
In 2012, Pakistan was producing over 20 billion liters of tradable white milk per year, making it the 3rd largest producer in the world. In 2013, Nestle issued a press release claiming a production capacity of half a billion liters of milk. It is estimated that Pakistan fails to meet local demand by up to five billion liters. So its not surprising that the promise the industry and its returns attracts business families. We spoke to Suleman Monnoo of the Monnoo Group regarding the decision to enter the high demand market, their USP and more recent endeavor to break into flavored milk.
I’ve heard shoppers say “Bonus wala Surf dedein” and ask “Powder wala Milk Pak hai?”, so we can assume that there exist established players in multiple high frequency CPG categories. How does a textile family gain interested to compete in the most cut throat one?
Anyone with the capital backing is after this space and yes, there are some established players in the mindsets of the masses. So education was our largest concern, as was ensuring product quality at a level that addresses the concerns of our rising educated audiences.
In 2008 we faced a crisis in the textile industry and to counter this, everyone was trying to diversify. At the time, Pakistan was the fifth largest producer of dairy in the world. After reading “I Too Had a Dream” by Dr. Verghese Kurie, my interest in the area was fueled. I learned that New Delhi’s sales as a city are equivalent to our entire country. We studied the category and found it advantageous to become the first in Sindh to enter dairy. Punjab has had it easy because of the processors in place, the drawback for us was the minimum requirement in volumes need to afford the required processors, which when unmet, can result in the product going bad. Our research reflects that 80% of consumption is loose milk. To avoid these issues, we set out to have our own farm.
The kind of infrastructure you’re referring to drives up costs. How did you mitigate this against the existing investment needed?
If market visits to India taught me anything, its that no MNC could beat me if I had the vision, because MNC’s have too many overheads coming with growth. At the moment, Nestle has collection centers in the radius of villages like Sahiwal. Along with Engo and Haleeb, they utilize a contractor system and the incentives rotten the game. So when the demand goes up and the contractor cannot meet it, the product is fabricated with fake shipments.
While studying MBA from IBA, I learned about corporate farming abroad, wherein the incentive’s for fraud is less and contractors are incentivized to provide the right product at the ethical volumes they can create. Demand is therefore generated based on these volumes instead of the other way around. This is evidently not the case here because we are currently the third largest creator and consumer of dairy in the world. The high frequency of consumption encouraged in the demand generation process creates an unnecessary strain on the contractor.
You’re not only competing with large players, but pre-purchased shelf space, a product that lasts longer than yours and an acquired taste to buffalo milk. What was your unique counter?
In this industry, raw material is a game changer. And yes, the local pallet is developed on buffalo milk instead of cow milk. But the cow is more economical and it’s milk is better for digestion. A buffalo eats more and produces less. A business family like ours thinks long term, invests in assets that are longer lasting and efficient. We imported cows from Australia because the local variety are hard to certify as legitimate. We brought in an expatriate farm manager and the corporate farming system (similar to Almarai) to ensure quality assurance and meeting of standards practiced in developed nations. Taimur Butt, the master franchiser of Red Mango, recently visited one of our farms and gained international clearance to use our products to create the his acclaimed frozen yogurt products.
Unbranded milk accounts for three quarters of the current market, so why invest so much in branding when the market is so fixated on tried & tested favorites?
That’s short term thinking and a middle class approach. A brand is a life line, its like a child. We invest in our children and eventually they in turn support us. It’s the same with DayFresh and the overall brand experience. My experience in textile has taught me that if you have the right product and can communicate it, you can sell anything. We also learned (the hard way) to play with price perceptions. Five years ago, milk was PKR 50 per liter; we priced ours at PKR 45 per liter and it backfired because consumers new to our brand considered this to be reflection of quality. Total plate counts (TPC) is the industry standard for measuring milk quality. When it exceeds 100k, it becomes unfit for long term human growth and consumption’s. At the expense of shelf life (one week), our product has a 50k while our competitors measure in the millions. For the retailer, low shelf life is a problem, so we have our own distribution centers and network as well. Luckily, trade level education campaigns have improved the adoption, and the name DayFresh, reflects the brand promise.
You’ve been in business eight years to date. What were your key challenges, and what do you think is driving the sustainability and adoption?
Like I said, a good product that is communicated well, will sell. We have the right raw material, are small enough to focus and deliver on promising. We are also small enough to respond to consumer needs and its very important in a product like milk. After being exposed to open air, milk goes bad pretty fast. So we pump our cows with automation and chill the milk to 4 degree Celsius to stall further bacterial growth. This commitment to high quality limits to shelf life, and its adoption by retailers is a challenge so we need to invest more in attaining touch point shelf space and our own distribution network.
Based on advertising messaging, we can safely postulate that flavored milk is aimed at children. A glance at local or international trade further shows that international players in the direct and indirect nutrition positioning dominate shelf space. Canteens at major schools and colleges have been branded with some of these for years. So what was the rationale behind entering flavored milk?
We think Pakola has done the best job in this category because they are exclusively focused on flavored milk and research points this to be a small category, expected to reach 20 billion liters in demand this year alone. We sought it out due to our increasing capacity and interest to tap new markets backed by retained earnings from DayFresh. The only downside is that the market is not that developed, and when you’re leading the charge, you’re also incurring costs.
While children are the end consumers, their parents – health conscious and concerned for long term health & safety – can be influenced by our campaigns. We are a trusted brand, so when we launch flavored milk backed with the same high quality infrastructure, parents trust us. Insights from our own delivery network indicate that our products are consumed as a key breakfast item, and chocolate or strawberry milk is more appealing to children than the plain alternative.
Thank you for your time Suleman, it was a pleasure.
- Successful Brands must Value and Empower Fans
- Neurobranding & Social Currencies in 2014
- Brand Management in an Unpredictable Digital Economy
Author: Babar Khan Javed, Tech Journalist at Express Tribune
Join FutureCMO Movement LinkedIn Group here
In the consumer good industry, your best bet is to be contextually relevant and meet the customer half way. I like cross selling like anyone else, but complimentary sales strategies are doubly effective.
TROJAN (condoms) next to baby food, as in “While you’re in this aisle, how about this mistake prevention mechanism?”
M&M’s in the feminine hygiene aisle, as in, “You might want to get here these as well and get bonus points for caring.”
Invest in conversion* marketing, points of sale data and shopper marketing. Raise awareness by engaging your target customer around a common cause or interest point – all positive.
Got any more ideas?
As we already know, organizations have ability to collect, store and analyze massive amount of data from multiple sources. They have spent a lot of money managing this big data. Investments in technology and analytics are useless unless employees can use data, information and knowledge in their decisions-making. Many companies are facing a big challenge in data-driven decision-making. Good and rich data won’t quarantee good decisions on their own. I posted May 2012 an article about Insight IQ. It was based on April 2012 issue of the Harvard Business Review where Shvetank Shah, Andrew Horn and Jaime Capella argue that Good Data Won’t Guarantee Good Decisions. In this article I continue this theme a bit further.
Shah, Horn and Capella found that there are three main types of decision makers:
- Visceral decision makers (gut feel decisions)
- Unquestioning empiricists (rely on the number alone)
- Informed skeptics (gut feel with data)
If we consider the matter in data perspective I defined simple data collaboration or data insight maturity scale. It emphasizes level and maturity of data collaboration in decision-making.
Organizations on the right ‘high side’ are capitalizing the data in decision-making. They combine the gut feel with data and can drive decisions that make a real difference in productivity and profitability. They can drive real competitive edge from and behind the data. They drive all necessary information from markets for better decision-making. They know their customers and customer journey. Although the decisions can be very complex with limited amount of time and there are many options to choose from, they can still make the decisions and carry out them fast. These companies are the winners. They have hit the jackpot, but unfortunately I see these kinds of companies quite seldom. However, that is the goal to go for.
Another way of looking at this variety in corporate behavior is to divide companies in three categories according to state of data maturity. There are three types of companies: data collectors, data analyzer and data innovators.
1. Data collectors
These companies are collecting and learning which data is important for their business. Light segmentation is used and it is more building and focusing on different customer groups. Analytical skills are very low and decisions are made as gut feel or based on basic sales figures and income statement
2. Data analyzer
These companies have systematic way of collecting and storing data. They are invested in the technologies that are available to analyze the data. They can do basic business reporting but are not able to drive the real value behind the data. They are good at analyzing and reporting but suffer the lack of interpretation skills to drive deeper business insight.
3. Data innovators
These companies are more comfortable with big data sets and technology. The focus is in how benefit from actionable insights and strategic big data. They have effective ways to share business information across functional areas that better decisions can be made. They have many data-savvy employees and data-driven decisions are informality in C-Suite.
Steps from data collector to data innovator
It is all about people, process and technology. Here are six steps to improve data-driven decision-making.
1. Emphasis on right data
- collect all relevant information into one single platform
- from business understanding to data understanding
- automate the data collection process
2. From silos to holistic business view
- map all the relevant data, which is essential for decision-making
- data preparation, consolidation and visualization are necessary
- CMO & CIO partnership
3. Choose the right technology
- find technology that meets your business demands
- choose technology, which accept and read data from any source
4. Online reality
- today’s business and business environment needs real-time data
- online data as enabler of quick decisions and insights
- rapid resource allocation
- online business management and intelligent decisions
5. Create strategic marketing dashboard
- KPI’s by channel
- true values from returns and investments
- identify risks and opportunities
- measure and lead the customer journey
6. Create systematic analytic skills competence development program for employees
- find the data-savvy workers in your organization
- make them to train everyone else of their analytics skills and method
- leverage analytics know-how widely in your organization
- C-suites as exemplary for others
I read a very interesting article from HBR, April 2012 issue. Shvetank Shah, Andrew Horne and Jaime Capella wrote an article about how good data won’t guarantee good decisions and most companies have too few analytics-savvy worker. If you are not able read that excellent article from HBR, here is a couple of points from it.
We have already discussed in this group about the new era of decision-making and importance of customer insight. Ability to collect, store and analyze the big data has grown explosively and companies spend a lot of money analyzing customer data. BUT. And this is a big but although you have the best BI tools ever but if your organization cannot capitalize it the investments are useless. Like Shah, Horne and Capella stated in the article: ”For all the breathless promises about the return on investment in Big Data, however, companies face a challenge. Investments in analytics can be useless, even harmful, unless employees can incorporate that data into complex decision-making. At this very moment, there’s an odds-on chance that someone in your organization is making a poor decision on the basis of the information that was enormously expensive to collect”
Shah, Horne and Canella created Insight IQ, method that asses the ability to find and analyze relevant information. They evaluate 5000 companies from 22 countries. The founding’s were interesting. Three groups were found: ”unquestioning empiricists”, visceral decision makers” and ”informed skeptics”
Companies are seeking for ”informed skeptics”. They are data-savvy workers who are able to make good decisions. They have strong analytic skills, ability to balance judgment and analysis. However, the study found that only 38% of employees and 50 % of senior managers fall into this group.
Shah, Horne and Canella identified four problems that prevent organizations from realizing better ROI in Big Data:
- Analytic skills are concentrated in too few employees
- IT needs to spend more time on the “I” and less on the “T”
- Reliable information exist, but it’s hard to find
- Business executives don’t manage information as well as they manage talent, capital and brand
Well, how to develop more informed skeptics? It demands constant competence development to increase data literacy and join information into decision-making. And of course, organizations have to give the right tools for analyzing the data. Ongoing coaching is essential and formalizing the decision-making process based on data and information. Shah, Horne and Capella stated that “many of the best data-driven cultures have formalized the decision-making process, setting up standard rules so that employees can get and correctly use the most appropriate data. Companies should make performance metrics transparent and embed the in job goals. They should also make sure that compensation systems reward dialogue and dissent. Great decisions often need diverse contributions, challenges, and second-guessing”.
Tiffany and BCBSNC are the great example of companies who have shown growing awareness of the pay-offs from Big Data and data literacy.
Is your organization underinvested in understanding the information and maximize Big Data ROI?
Source: Harvard Business Review April 2012,
Article: Good Data Won’t Guarantee Good Decisions
Writers: Shvetank Shah who leads the information technology practice at Corporate Executive Board, Andrew Horne and Jaime Capella, who anre managing directors at Corporate Executive Board