Techaisle Analyst Insights

What is the market mix problem that I keep talking about that has stayed unsolved for so many years. The problem by itself is simple: How much does my brand sell for different marketing inputs? A regression model needs historical data of at least three years. Most companies either do not have that much data, or the markets have changed in three years and hence the data is pretty much useless. In addition, regression models cannot accommodate changes in product formulation or advertising campaign changes. Further, economic data like GDP, CPI and inflation can never be built into the regression model. Hence all statistical modeling leads you up a cul-de-sac.

So what did I do that was so different? I went back to market research data. Almost all companies do advertising or brand tracking. The sample sizes in these tracks vary from 800 to 4000, every month. The tracks capture primarily the exposure to media, awareness of advertising and the brands, brand imagery and Intention to buy. They set up benchmarks against each parameter and take marketing decisions. For example: if the claimed exposure to TV in April is 30% and it was 40% in March, they call the advertising agency and ask them to change the channels. If the imagery is not improving then they will change the advertising. These decisions are ad hoc, because they have no clue on how each of these decisions will affect a priori. The marketing guy’s knowledge is always from hindsight. So, what we did was to pick up the brand track data with 800 or 4000 respondents and modeled it. The basic modules were:

1. Exposure to Awareness Model

1. Awareness to Image Model

1. Image to Intention to buy Model

1. Intention to buy to actual sales model

With this approach we had solved one two problems: The requirement of long history of the brand’s performance and the irrelevance of historical data to the current scenario. We could take the brand track data from April and model it for May. Nothing can be more recent than this.

Now came the tricky part. How does one link media and other marketing inputs. This was done through a heuristic algorithm. Each respondent in the track was assigned a value for each marketing input. Now we had a file with track and inputs in each record. After this it was easy to integrate all other data. Once we had all the data together the independent modules were built using ANN and a dash-board was designed to make life easy for the user.

What were the results? Based on each month’s inputs we estimated the sales. What we could deliver was 85-95% accuracy of forecasts compared to the company’s sales-out figures. This far exceeded the original mandate to deliver a solution that gave 75% accuracy.

How does this help the brand managers? Here is a list.

1. Understanding of the brand characteristics using the tabulator cuts down the time of extracting information from different sources by 80%.

1. Simulate the brand response to variations in brand inputs to get the optimum response.

1. If there is a competition activity in the market it is possible to check what investments should they make to reduce the effect of these activities on their own brand.

1. Use the simulator during brand and advertising reviews.

Our Brand Modeling solution is a huge help in effective planning of a brand to meet the targets. With our unique Brand Modeling Solution a 30-year-old problem that brand marketers have been grappling with was put to rest. We have a successful solution.

Dr. Cooram Ramacharlu Sridhar (Doc)
Techaisle

They are here - Techaisle's annual SMB and Midmarket Top 10 IT Priorities, IT Challenges and Business Issues infographics. This is the 7th year of Techaisle tracking at a WW level and is much sought after by IT vendors, channels and media. There is an ongoing trend – in both the buy-side and supplier communities – towards positioning IT initiatives and expenditures in a business context.

To help readers connect positioning with core market drivers, Techaisle research provides insight into the most pressing business issues, IT priorities and IT challenges faced by small (1-99 employees) and midmarket (100-999 employees) businesses in 2018.

For 2018, Techaisle investigated 21 different technology areas, each with several sub-technology categories, 24 different IT challenges and 24 different business issues. At the request of our clients, this year, not only are we releasing data & infographics (shown below) as usual for SMBs (1-999 employee segment), Midmarket (100-999 employee segment) but also for Small businesses (1-99 employee segment).

In 2018, the new and upcoming IT Priorities within SMBs are Virtual Reality (VR)/Augmented Reality (AR) and Hyperconverged infrastructure (HCI). Within midmarket firms, Artificial Intelligence (AI) appears for the first time for 2018. Workplace transformation is one of the new top IT challenges for SMBs – number 1 on the list for midmarket firms and overall at number six across all SMBs. This obviously points to a need for unified workspace experience. In addition, Cloud orchestration and integration are among the top five key IT challenges for both SMBs and midmarket firms.

Generative Artificial Intelligence (GenAI) is on the brink of a massive expansion. IBM is seizing this opportunity and striving to cater to the escalating demand for this technology. The company has launched watsonx, an AI and data platform specifically designed for businesses, providing GenAI, data management, and AI model governance capabilities.

IBM’s strategic efforts go beyond mere product innovation. They include collaborative ventures aimed at stimulating growth across the industry. The company’s new partner program, IBM Partner Plus, is designed to establish a diverse network of resellers. This initiative is set to ignite growth and spur innovation in various sectors, highlighting IBM’s commitment to making AI accessible and enabling businesses around the globe.

IBM's Journey with watsonx and Responsible AI Governance

Partnerships and acquisitions frequently serve as turning points, transforming entire industries. This is exemplified by IBM’s 2019 acquisition of Red Hat, a prominent provider of open-source software solutions. This strategic move has fortified IBM’s standing in the open hybrid cloud solutions market while simultaneously offering both companies the chance to provide their clients with improved AI capabilities. IBM watsonx is an AI and data platform with a set of AI assistants designed to help organizations scale and accelerate the impact of AI with trusted data across the business. The platform offers flexibility, enabling organizations to start with one component or application and include additional ones as needs grow. It consists of a studio for foundation models, a data store, and a governance toolkit.

In an era of globalization, businesses often pursue economies of scale and standardized solutions. Zoho, a global software behemoth with Indian origins, is carving a distinctive path. It has embraced a unique business strategy known as “transnational localism.” This approach intertwines global connectivity and local grounding, fostering local economies while partaking in the exchange of knowledge and culture. Transnational localism, as defined by Zoho, is a decentralized strategy that harnesses the benefits of a global scale while maintaining deep roots in local communities. It transcends the conventional “think global, act local” mantra, offering a more nuanced and influential method to tackle today’s complexities. This strategy is implemented through a tripartite approach:

• Developing a Global Technology Stack: Zoho creates its software products suite, ensuring total control and adaptability.
• Empowering Local Teams: Zoho sets up regional offices staffed with local talent, enabling them to tailor solutions to specific market requirements.
• Prioritizing Local Communities: Zoho invests in local talent development, infrastructure, and social initiatives, nurturing a sense of collective responsibility and growth.

Transnational localism strikes a balance between global outreach and local engagement. It involves establishing offices in less affluent locations globally, injecting investment, expenditure, and job creation into these areas. The company stays globally connected, not just digitally, but also through a shared ethos and culture, while remaining locally anchored.

Zoho’s CEO, Sridhar Vembu, characterizes transnational localism as a strategy that sources talent from regions often neglected by other companies. These are typically areas experiencing talent emigration, leading to hollow communities. Zoho strives to reintroduce opportunities into these regions, commonly drained into urban centers.

Beyond the Numbers: Real-World Examples

Zoho’s dedication to transnational localism extends beyond mere theory. It has actualized this philosophy by setting up a global network of over 25 offices in rural areas. Many IT suppliers overlook these locations for opportunities compared to their metropolitan counterparts. For instance, Zoho has an office in McAllen, Texas, with nearly 150,000 residents within a metropolitan area housing over a million people.

Another notable instance is Tenkasi in India, where Zoho inaugurated its first rural office. Despite being a city of nearly 100,000 people, Tenkasi is considered rural compared to India’s major metropolitan areas. In Tenkasi, Zoho operates a remote farm and an elementary school, both flagship initiatives in its rural revival strategy.

Zoho demonstrates its commitment to social responsibility in several ways. It has invested in rural India through its "10,000 Schools" program, which bridges the digital divide by providing digital infrastructure and training to schools. Additionally, Zoho empowers local communities by establishing offices in smaller towns across the US and Europe, fostering diversity and creating local job opportunities. Finally, Zoho tailors its product suite to specific market needs, showcasing its commitment to global inclusivity by respecting cultural and regulatory contexts.

The Impact on Zoho's Business: A Multi-Faceted Success Story

Transnational localism has significantly influenced Zoho’s business, propelling its remarkable growth. By the end of 2021, Zoho had amassed 500,000 customers, over 70 million users, and 40,000 customers on Zoho One, a product launched in 2017. One of these customers had 32,000 employees utilizing Zoho One. Fast-forwarding to 2024, Zoho’s customer base has expanded to over 750,000, with over 100 million users across 150+ countries.